Engineering
what moves
your business.
Negits Solutions delivers across two industry verticals — Automotive and Enterprise Systems — unified by a horizontal AI practice spanning generative AI, LLMs, RAG, MCP, and agentic systems. From sensor to seat to ledger to copilot.
Two verticals. One AI practice across both.
Automotive
Autonomy, cockpit, and software-defined vehicle platforms for OEMs, Tier-1s, and mobility operators. From perception to planning to cabin UX.
Enterprise Systems
Finance, People, GTM, Data, DevOps, and the integration fabric — with L1/L2/L3 service delivery and a dedicated PROD support desk.
AI Practice
Generative AI, LLMs & SLMs, retrieval-augmented generation, Model Context Protocol, and agentic systems — applied across both verticals.
Productized building blocks
Reference platforms, reusable components, and reference designs that compress months of integration work — across both verticals.
Strategy to SOP
Executive advisory, hands-on engineering, due diligence, functional safety, talent & org, and APQP/PPAP/SOP delivery.
Industry solutions
Pre-architected reference solutions across passenger OEM, commercial trucking, robotaxi, off-highway, robotics, and Tier-1.
Mobility, and the enterprises that run it.
From passenger cars and commercial trucks to off-highway and embodied robotics — and across the enterprise systems that finance, plan, sell, and serve them. The autonomy, cockpit, and AI primitives are converging with enterprise operations.
From feasibility study to start-of-production — one partner across the stack.
Eight countries. Credentialed everywhere.
Headquartered in Singapore. Delivery centers across NAFTA, EMEA, India, and APAC. Certified partner of AWS, Microsoft, Snowflake, SAP, Workato, Fivetran, Talend, Atlassian — and engineering partner of NVIDIA, Qualcomm, and QNX.
The automotive vertical.
From sensor input to actuator output, from cabin pixel to vehicle motion — Negits delivers production-grade autonomy, cockpit, and software-defined-vehicle platforms for OEMs, Tier-1s, and mobility operators.
Autonomy. Cockpit. Platform.
Autonomy
Production-grade ADAS / AD stack — perception, prediction, planning, and control. Modular, hybrid E2E, and pure E2E architectures from L2+ through L4.
Cockpit
Multi-display HMI, in-cabin AI, voice agents, DMS/OMS, and personalization — consolidated on a single high-performance SoC.
Platform & SoC
NVIDIA DRIVE, Qualcomm Ride, hypervisors, AUTOSAR, AI foundation models, and the zonal E/E architecture beneath everything.
From photon to wheel torque.
The full automotive vertical — one partner.
The drive stack.
A production-grade autonomy stack from sensor input to actuator output — architected for SAE L2+ through L4, validated against ISO 26262 and SOTIF, deployable on NVIDIA, Qualcomm, or hybrid SoC platforms.
Three architectural patterns. One delivery philosophy.
Modular
Classical perception → prediction → planning → control pipeline. Maximum interpretability, deterministic safety case, mature certification path. The default for L2+ ADAS programs.
Hybrid E2E
Neural perception and prediction with a learned policy head, paired with a rule-based safety filter. The pragmatic balance of scalability and certifiability for L3 highway and urban.
Pure E2E / VLA
Vision-language-action models trained on internet-scale and fleet data, with closed-loop world-model validation. The frontier — Wayve, Tesla FSD, and emerging foundation-model autonomy.
Eight layers, one signal path from photon to wheel torque.
Heterogeneous sensing, fused with intent.
No single modality is sufficient. We design sensor sets and fusion strategies that exploit each modality's physics — and degrade gracefully when one fails.
Cameras
120 dB dynamic range
30/60 fps
Surround + long-range
Imaging Radar
300+ m range
Velocity & elevation
All-weather
Lidar
1550 nm preferred
200+ m at 10% reflectivity
Sparse to dense fusion
Ultrasonics
Parking, low-speed
Curb detection
Redundant near-field
GNSS-INS
Tightly coupled IMU
cm-grade lateral
Dead-reckoning fallback
V2X
DSRC where mandated
5G-Advanced uplink
HD-map updates
Thermal / NIR
VRU detection at night
Glare immunity
Optional L4 sensor
Wheel + IMU
6-DOF IMU
Vehicle dynamics
Odometry fusion
From L2 features to L4 mission profiles.
ACC · LKA · AEB
Adaptive cruise, lane-keep assist, automatic emergency braking with vulnerable-road-user detection. NCAP-tuned for 5-star ratings.
HWA · TJA
Highway assist and traffic-jam assist with hands-on monitoring and confidence-aware ODD enforcement.
Navigate-on-Pilot
Mapless or HD-map-assisted urban and highway pilot with lane-change automation and route-aware planning.
Parking & summon
Memory-parking, autonomous valet, in-spot maneuvers, and trained-path summon for home and structured lots.
Eyes-off highway
Conditional autonomy with full driver disengagement on mapped, geofenced highway segments. UNECE R157 compliant.
Robotaxi · shuttle
Driverless operation in defined ODDs with remote assistance, MRM handling, and full data-flywheel continuous improvement.
Bring your perception bottleneck, planner gap, or full-stack ambition.
Seeing the world as it is.
Multi-sensor perception built on BEV transformer backbones — converting raw pixels, radar returns, and lidar points into a unified, temporally-consistent representation that planners can act on.
BEV transformers, not patchworks.
A single unified backbone replaces the legacy stack of independent detectors. We deploy BEVFormer-class architectures fine-tuned for production constraints — latency, memory, and quantization-friendly operators.
Camera-only BEV
Spatial cross-attention from multi-view cameras into a unified BEV grid, with temporal self-attention across frames for velocity and occlusion handling.
Camera + lidar
Modality-agnostic fusion in BEV space; lidar features and image features are projected to the same grid and fused with learned cross-attention.
End-to-end multi-task
Unified perception + prediction + planning heads sharing a common BEV backbone — gradient flow from planning loss improves upstream perception.
3D semantic occupancy
Dense 3D occupancy networks predict per-voxel class and motion; complementary to bounding-box detection for general-obstacle handling.
Everything the planner needs, in one forward pass.
| 3D object detection | Vehicles, VRUs, animals · class, position, dimensions, orientation, velocity, attributes 9-DOF |
| Multi-object tracking | Cross-frame association, ID stability, trajectory smoothing <1% ID swap |
| Lane graph | Vectorized lane centerlines + topology + traffic-light association 100 m horizon |
| Free-space & drivable area | Dense BEV segmentation with confidence 0.1 m resolution |
| 3D occupancy | Semantic voxel grid with motion estimates 200 × 200 × 16 |
| Traffic signs & lights | Detection, classification, state, association to lanes 200 m max |
From training cluster to SoC silicon.
QAT to INT8 / FP8
Quantization-aware training preserves > 98% of FP32 accuracy. Export pipelines for TensorRT, QNN, OpenVINO, and SNPE.
Bounded inference
30 ms perception cycle on DRIVE Thor; 50 ms on Qualcomm Ride. Per-batch determinism for safety-critical workloads.
Sensor degradation
Graceful degradation when sensors fail — covariance-aware fusion drops confidence rather than the whole perception output.
Closed-loop validation
Replay over millions of fleet miles; world-model-generated rare events; full integration with the LoopYard simulation pipeline.
Perception is the load-bearing wall of the autonomy stack.
From intent to actuation.
A hierarchical planner that turns perception output and route intent into a smooth, safe, comfortable trajectory — and a high-rate controller that tracks it within actuator limits.
Three layers. Each with the right horizon.
Mission-level
OSM- and HD-map-aware route planning. Charging, tolls, traffic, and ODD-aware. Re-routing on the order of seconds.
Tactical layer
Lane selection, gap acceptance, merge intent, intersection negotiation. 3–10 second horizon, decisions every 100 ms.
Trajectory optimization
Continuous-space trajectory generation under kinematic, dynamic, and comfort constraints. 100 Hz, 4–6 second horizon.
Actuator-level
NMPC and H-infinity controllers tracking the planned trajectory at 200–500 Hz with actuator-aware command shaping.
The mathematics, without the romance.
| Motion planner | Sample-based + optimization-based hybrid; NMPC with terminal cost, soft and hard constraints IPOPT / OSQP |
| Lateral control | Model predictive control with curvature-feedforward; backup pure-pursuit + Stanley ±5 cm lateral |
| Longitudinal control | PID with feedforward jerk-limited shaping; vehicle-dynamics-aware brake/throttle blending ±0.1 m/s |
| Comfort metric | Bounded jerk, lateral acceleration, and angular rate; ISO 2631 weighted <2.5 m/s³ |
| Fallback planner | Hardcoded policy + RSS envelope; activated on perception confidence loss ASIL D |
| MRM library | Minimum-risk maneuvers: in-lane stop, shoulder pull, controlled deceleration UNECE R157 |
Hybrid, by design.
Pure learned planners are scalable but hard to certify. Pure rule-based planners are certifiable but brittle. Our reference architecture pairs a learned policy (proposals, comfort, urban naturalness) with a rule-based safety filter (constraints, fallback, ASIL D supervisor) — production-grade and provably safe.
Where most stacks show their seams — long-tail urban planning.
Photons, returns, and physics.
Sensor selection is the single biggest determinant of system cost, performance, and ODD coverage. We design heterogeneous sensor sets matched to each program's commercial and technical reality.
Each sensor's signal, each sensor's failure mode.
High resolution, semantic-rich
8 MP HDR, 120 dB dynamic range, rolling-shutter-compensated. Excellent for classification, lanes, signs. Fails on glare, night, fog.
All-weather, velocity-native
4D MIMO 76–81 GHz, 300+ m range, native Doppler. Robust to weather and lighting. Lower angular resolution than camera.
Geometric truth
1550 nm preferred for eye-safety at higher power. 200 m at 10% reflectivity. Excellent for 3D structure. Cost and dust/rain sensitivity remain considerations.
Night-time VRU detection
8–14 μm LWIR. Detects pedestrians and animals through darkness and glare. Optional L4 sensor; mandated in some jurisdictions.
Near-field
Short range (< 5 m), low cost, redundant. Indispensable for parking and curb-side maneuvering.
Global position
RTK / PPP with tightly-coupled IMU. cm-grade lateral. Critical for HD-map-anchored lane-level localization.
The right set for the program.
| L2+ Highway / NoP | 5–8 cameras · 3–5 radars · 12 ultrasonic Volume tier |
| L2+ Urban NoP | 8–11 cameras · 5–6 imaging radars · 12 ultrasonic · optional 1 lidar Premium tier |
| L3 Highway | 11 cameras · 5 imaging radars · 1–3 lidars · GNSS-INS · 12 ultrasonic Flagship tier |
| L4 Urban Robotaxi | 11+ cameras · 6+ radars · 3–7 lidars · thermal · cm-GNSS · redundancy Driverless grade |
| L4 Trucking | Long-range lidar & radar · 360° camera · cm-GNSS · redundant compute Commercial grade |
Calibration, sync, and the unsexy work.
Factory + online
Targeted factory calibration with online refinement. Extrinsic, intrinsic, temporal, and inter-sensor.
PTP-grade alignment
IEEE 1588 across sensors with < 1 ms jitter for the safety-critical chain.
Heterogeneous redundancy
Diverse-redundant sensing — never two failures from the same cause taking down both channels.
Self-diagnostics
Continuous quality monitoring; degraded modes communicated to fusion and the safety supervisor.
Tell us your ODD. We'll spec the sensor set.
Features that ship, scored by NCAP.
Production-tuned ADAS features calibrated for Euro NCAP, IIHS, and C-NCAP test protocols — and engineered for real-world ODDs, not just the test track.
The features that save lives and pass NCAP.
Automatic emergency braking
Vehicle, VRU (pedestrian + cyclist), and motorcyclist scenarios. Day, night, and junction. Tuned for Euro NCAP 2026 + C-NCAP.
Forward collision warning
Multi-stage haptic + audible + visual escalation. Calibrated TTC thresholds for low false-positive rate.
Blind spot & rear cross-traffic
Radar-based detection of approaching vehicles in blind zones and at reverse maneuvers.
Door-opening assist
Radar/camera-based warning before door release; mandatory in some NCAP protocols from 2026.
The features customers actually use daily.
Adaptive cruise
Full-speed-range adaptive cruise with stop-and-go. Smooth gap-keeping calibrated by region preferences.
Lane-keeping + centering
Hands-on lane-centering with curve-prediction and lane-change automation. Map-aided where HD maps are available.
Traffic-jam & highway assist
L2+ assisted driving on highway and congested traffic with confidence-aware ODD enforcement.
Navigate-on-pilot
Map-aware highway pilot that handles ramps, interchanges, and lane changes to follow a navigation route.
APA · RPA · Memory · AVP
Automated parking, remote summon, memory-parking on trained paths, and autonomous valet in equipped facilities.
City driving assist
The frontier — mapless or HD-map urban pilot with intersection negotiation. L2+ on the way to L3.
When the driver can look away.
L3 and above demand a different safety case — the driver is no longer the fallback. We build the architecture, the safety case, and the type-approval package for UNECE R157 (highway L3) and equivalent jurisdictions for L4.
Score 5 stars. And ship.
Audit-survivable. Type-approved.
ISO 26262, ISO 21448 SOTIF, UNECE R155/R156 cybersecurity, and UNECE R157 type approval — practical, OEM-tailored, and built into the engineering process from day one.
Functional safety, without the theater.
Hazard analysis
Systematic identification of vehicle-level hazards; severity, exposure, controllability → ASIL determination.
ASIL decomposition
Allocating ASIL D goals to combinations of lower-ASIL elements with provable independence.
Failure analysis
FMEDA for hardware, FTA for systemic faults, with measurable diagnostic coverage targets.
Tool qualification
TCL 1 / 2 / 3 qualification for all tools in the safety-critical pipeline — compilers, generators, verifiers.
SOTIF — the known unknowns.
Functional safety covers what fails. SOTIF covers what works as designed but produces an unsafe outcome — sensor blindness, edge-case behavior, machine-learning brittleness. For ADAS and AD systems, SOTIF is where most of the engineering rigor actually lives.
| Triggering conditions | Systematic identification of scene conditions that drive the system out of its ODD 3000+ cataloged |
| Acceptance criteria | Per-feature performance criteria tied to PRB and PFB rates FMVSS / GSR |
| Validation campaigns | Sim + closed-course + open-road; statistical sufficiency by ODD Bayesian release-gate |
| Residual risk | Quantified, justified, and gated through release review SAE J3237 |
UNECE R155 + R156, by design.
R155 management system
Threat analysis, monitoring, and incident response. Required for type approval since 2024.
R156 update system
Secure software update management — signed, rolled-back-able, ECU-by-ECU validated.
Hardware roots-of-trust
Key management, secure boot, debug-port lockdown. Integrated with the platform from boot stage 0.
Intrusion detection
Per-bus and per-ECU anomaly detection feeding fleet-level SOC dashboards.
An auditor we'd welcome, not endure.
The cabin as a product.
Multi-display HMI, in-cabin AI, voice agents, and personalization — consolidated on a single high-performance SoC and orchestrated as one continuous user experience.
Pillar-to-pillar, glanceable, contextual.
Cluster, central infotainment, passenger display, head-up display, and rear-seat entertainment driven from a single graphics domain. Wayland or QNX-screen compositing, GPU partitioning, and per-display safety isolation.
- Display partitioningHypervisor-isolated
- HUDAR, 10–15° FOV
- Refresh / latency60–120 Hz, <16 ms
- Cluster safety classASIL B
One SoC. One HPC island.
Consolidate cluster, IVI, ADAS coexistence, and cabin AI on Qualcomm Snapdragon Ride Flex / Cockpit Elite or NVIDIA DRIVE Thor. Hypervisor partitioning between QNX, Linux, and Android Automotive. Mixed-criticality, deterministic boot, and safety-rated graphics.
- HypervisorQNX · Wind River · COQOS
- Guest OSAAOS · Linux · QNX
- GPU virtualizationVulkan, multi-tenant
- SafetyASIL B in mixed criticality
A78AE × 12
Adreno / Ada
30–60 TOPS
multi-camera
The cabin knows who, where, and how.
Driver monitoring (DMS) for drowsiness, distraction, and attention; occupant monitoring (OMS) for child presence, seat-belt status, gesture, and emotion. Compliant with EU GSR-2 and Euro NCAP 2026+ protocols.
- DMS modalityNIR camera + ToF
- OMSRGB-IR + radar CPD
- Latency< 100 ms drowsiness
- RegulatoryGSR-2 · NCAP 2026
Multimodal, anticipatory, agentic.
A unified HMI layer spanning touch, voice, gesture, and gaze. On-device wake-word and ASR with hybrid cloud LLM for complex intent. Personalized profiles, biometric handoff, and a voice agent that completes tasks rather than reciting options.
- Voice stackOn-device + cloud LLM
- Wake-word latency< 200 ms
- Multimodalgaze + voice + gesture
- Personalizationbiometric profiles
Differentiate your brand where customers actually live — the cabin.
Pillar to pillar. Glanceable.
The display surface is the canvas of the modern cabin. Cluster, central, passenger, HUD, and rear-seat — driven from one SoC, composited as one experience, isolated for safety where it matters.
Up to six surfaces, one composer.
Driver instrument cluster
10–13" curved or flat. ASIL B safety class for tell-tales. Hard real-time rendering with deterministic boot.
Infotainment
12–17", optional second row. Connected services, navigation, media, vehicle settings. Best of phone-projection + native experience.
Front passenger display
Privacy-filter optional. Independent media playback. Pairs with rear-seat for shared experiences.
AR head-up display
10–15° FOV AR HUD with depth-correct overlays for navigation, hazard, and ADAS state.
Rear entertainment
Per-seat content with parental controls. Wireless audio routing to in-cabin and Bluetooth headphones.
Optional exterior displays
Welcome screens, EV charge status, V2X intent signaling for VRUs in shared-space environments.
| Refresh rate | 60–120 Hz depending on surface and content VRR supported |
| Latency budget | Touch-to-pixel < 50 ms for primary HMI, < 16 ms for cluster Wayland / QNX-screen |
| Color & HDR | DCI-P3 90%+ coverage; HDR10 for media; calibrated cluster gamut Δ E < 2 |
| Safety isolation | Cluster partition independent of IVI; freeze detection & failover ASIL B |
| HUD optics | Picture-generating unit + freeform mirror; thermally-stable optical path AR / virtual image |
Displays are the brand customers see every day.
One SoC. Mixed criticality.
Consolidating cluster, IVI, DMS/OMS, and (optionally) ADAS onto a single high-performance SoC — under a Type-1 hypervisor with deterministic partitioning between safety-rated and consumer-grade workloads.
Best-of-class, by program reality.
Snapdragon Cockpit Elite Gen 4
Class-leading multi-display, NPU-accelerated AI, integrated modem. Industry standard for premium cockpit programs.
Ride Flex
Cockpit + ADAS consolidation in a single SoC family. Ride and Cockpit pin-compatible — significant BOM savings.
DRIVE Thor
Centralized SDV brain. AI throughput on the order of 2,000 TOPS. Pairs cockpit and ADAS at the highest performance tier.
Cost-sensitive tiers
R-Car V4H, TDA4VH and similar for entry and mid-tier cockpit. Lighter feature set, attractive cost.
The boundary between safety and experience.
| Hypervisor | QNX Hypervisor (default for safety-rated) · Wind River Helix · COQOS · Xen for cost-tier Type-1 |
| Guest OS | QNX (cluster) · Android Automotive (IVI) · Linux (services) · safety-RTOS (supervisor) 3–5 guests |
| GPU virtualization | Time-sliced or partitioned; Vulkan / OpenGL passthrough where supported multi-tenant |
| Mixed criticality | ASIL B for cluster within a mixed-criticality SoC Freedom from interference |
| Boot & failover | Cluster up < 1.5 s; IVI < 8 s; cluster freeze detection with redundant tell-tale path Deterministic |
Consolidate. Without compromising safety.
The cabin knows.
Driver and occupant monitoring meeting EU GSR-2, Euro NCAP 2026+, and emerging US/China protocols — with on-device inference and a UX that respects privacy.
Eyelid & gaze patterns
PERCLOS, blink rate, head-pose stability. Multi-stage alert with hand-off recommendation. < 100 ms latency.
Eyes-off-road & phone use
Gaze-zone classification, phone-in-hand detection, conversation-with-passenger awareness.
Anomaly detection
Behavioral deviation from baseline; medical emergency detection with optional auto-pull-over (with L3+).
L2+ engagement supervision
Mandatory eye-on-road monitoring during automated driving; enforced takeover request and ODD exit handling.
Child presence detection
Radar-based detection of unattended children — mandatory in EU GSR-2 from 2026. Robust through blankets, car-seats.
Occupant classification
Per-seat occupant detection & class (adult, child, none) for seat-belt reminder and airbag tuning.
In-air controls
Audio volume, media skip, accept-call gestures. Anti-confusion with driver motion.
Optional affective sensing
For wellness, content recommendation, and cabin-environment adaptation. Privacy controls mandatory.
| DMS sensor | NIR camera (940 nm) + optional ToF; behind-the-wheel mounting 10–15 fps |
| OMS sensor | RGB-IR + radar CPD; pillar or rear-view-mirror mounted Wide FOV |
| Inference | On-device, on NPU; no cloud round-trip for safety functions < 50 ms |
| Regulatory | EU GSR-2 · Euro NCAP 2026 · C-NCAP · UNECE R152 Test-ready |
| Privacy | On-device only · no recording by default · driver opt-in for analytics GDPR |
Compliance + experience, without surveillance creep.
Multimodal. Agentic. Personal.
A unified human-machine interface spanning touch, voice, gesture, and gaze — with an in-cabin agent that completes tasks instead of reading menus.
Use whichever modality is fastest right now.
Direct manipulation
Haptic-accented capacitive screens with predictable, large-target affordances. Glance-time-optimized layouts.
Continuous, conversational
Always-on wake-word with on-device SLM and cloud LLM fallback. Multi-turn intent. No more rigid command trees.
Mid-air shortcuts
A handful of high-value gestures — volume, skip, accept call. Distinct from driving motion.
Attention-aware UI
UI elements that surface when you look at a region. Driver-only on the cluster; passenger-aware on the central display.
| Wake-word | On-device, < 200 ms response, < 1% false-acceptance multi-keyword |
| ASR | On-device streaming + cloud fallback for long-form multi-language |
| NLU / dialog | Hybrid: deterministic for vehicle commands, LLM for open intent tool-use |
| TTS | Neural voice with brand-specific persona; sub-300 ms latency expressive |
| Languages | Localized for 30+ markets, with regional accent & idiom tuning A/B tunable |
The car knows who you are.
Biometric profile handoff (face, voice, phone-key) restores seat, mirrors, HVAC, audio, navigation, media, and assistant memory on entry. Profiles roam to other cars in the same brand. Privacy controls let any occupant disable personalization with a single touch.
An HMI that respects the cognitive load of driving.
Silicon, software, and AI.
The compute substrate beneath every modern vehicle program — heterogeneous SoCs, hypervisors, middleware, and the AI models that turn pixels and radar returns into decisions.
SoC-agnostic. Performance-aware.
We build on the platforms that production programs ship on. Our reference designs are tuned for each SoC's compute fabric, memory hierarchy, and safety story — no generic "ports" that leave performance on the table.
NVIDIA DRIVE
L2+ → L4From DRIVE Orin in production today to DRIVE Thor for centralized SDV. CUDA, TensorRT, and DriveOS optimized for transformer-heavy perception workloads.
- DRIVE Thor~2,000 TOPS · 2025+
- DRIVE Orin-X254 TOPS · in production
- DriveOSQNX or Linux · ASIL D
- ToolchainCUDA · TensorRT · NCCL
- Best forCentralized AV · cockpit fusion
Qualcomm Ride / Cockpit
L2 → L3Snapdragon Ride for ADAS, Cockpit Elite and Ride Flex for cockpit + ADAS consolidation. Industry-leading power efficiency and modem integration.
- Ride Flex / Elite~700 TOPS · SoC
- Cockpit Elite Gen 4multi-display · NPU
- OSQNX · AAOS · Linux
- ToolchainQAIRT · SNPE
- Best forCost-efficient cockpit + ADAS
We also deliver on Mobileye EyeQ Ultra, Horizon Robotics Journey 6, TI TDA4VH, Renesas R-Car V4H, and Ambarella CV3 where the program demands it.
The software-defined vehicle, end to end.
Hypervisor
QNX Hypervisor, Wind River Helix, COQOS — partitioning safety, infotainment, and AI workloads with deterministic isolation.
AUTOSAR Adaptive
Service-oriented architecture, SOME/IP, DDS, ara::com — the backbone of modern E/E architectures.
ROS 2 + custom
ROS 2 for prototyping and R&D, hardened production runtimes for series deployment with bounded latency and memory.
OTA & telemetry
Differential, signed, multi-ECU OTA updates with rollback. Telemetry pipelines feeding the data flywheel.
Simulation & training
CARLA, NVIDIA Omniverse / Cosmos, scenario libraries, distributed training on H100/H200 clusters, closed-loop replay.
UNECE R155 / R156
HSM key management, secure boot, intrusion detection, CSMS and SUMS compliance for type approval.
Foundation models, world models, agents.
Modern autonomy and cockpit run on three classes of AI working together: perception backbones, generative world models, and agentic policies.
BEV transformers
BEVFormer, BEVFusion, UniAD-style end-to-end perception with temporal attention and multi-task heads — detection, tracking, occupancy, lane graph in one network.
World models
GAIA-2, NVIDIA Cosmos, and custom generative simulators producing controllable, photoreal driving footage for closed-loop validation and rare-event synthesis.
VLA models
Vision-language-action policies trained on fleet data with language conditioning — the architectural pattern behind Wayve, Tesla v12+, and emerging E2E stacks.
From assistants to autonomous agents in the cabin.
The cockpit voice assistant is becoming an agent — one that takes goals, reasons over tools, and acts. We design the agent layer that closes the loop between the user, the vehicle, and the outside world.
LLM + tool-use
On-device SLMs for low-latency intent, cloud LLM for reasoning. Tool registry covering navigation, charging, calendar, smart-home, payments, and vehicle settings.
Memory & profiles
Per-occupant memory, calendar and routine awareness, and a privacy-aware context graph that disappears when the user leaves the vehicle.
Guardrails
Tool-use policy, output filtering, and clear delegation lines between agent suggestions and driver-confirmed actions — especially when actions affect vehicle motion.
Drive-level agency
"Take me home avoiding tolls and find a charger I'll reach with 15%." Agents that plan routes, reserve infrastructure, and brief the autonomy stack with high-level intent.
Operational agents
For commercial and robotaxi fleets — dispatch, remote assistance, predictive maintenance, and customer-facing agents handling routine exceptions autonomously.
Agent evaluation
Scenario benchmarks, jailbreak resistance, hallucination metrics, and a continuous-improvement loop wired to product analytics.
Build on a platform that survives the next generation.
The centralized SDV brain.
DRIVE Orin in production today, DRIVE Thor for the next generation. CUDA, TensorRT, and DriveOS — the platform of choice for transformer-heavy perception, world-model inference, and cockpit-AD consolidation at the top end.
| DRIVE Thor | Next-gen centralized AV+cockpit SoC; Blackwell-class GPU + transformer-engine ~2,000 TOPS |
| DRIVE Orin-X | Production SoC powering numerous current programs 254 TOPS |
| DRIVE Orin-N | Mid-tier variant for L2+ feature sets 100–200 TOPS |
| Safety | Lockstep CPU cluster, ECC across the memory hierarchy ASIL D capable |
| I/O | 16+ camera lanes, 10G automotive Ethernet, PCIe Gen 4 Multi-sensor |
DriveOS, and the CUDA ecosystem.
Safety-rated foundation
QNX or Linux base, hypervisor support, safety-rated drivers and middleware integrated.
Sensor & perception SDK
Camera, radar, lidar drivers, calibration tooling, and reference perception pipelines.
Inference toolchain
The most mature ML inference stack in automotive. Quantization, fusion, and graph optimization.
Sim & world models
Drive Sim, Omniverse Replicator, and Cosmos world models for closed-loop validation.
DRIVE is the platform when the program demands maximum AI throughput — L4 robotaxi, premium L3 highway, foundation-model-based stacks, and centralized SDV brains that fuse cockpit and ADAS. The CUDA ecosystem advantage compounds across the engineering lifecycle.
If you're building on DRIVE, we've shipped on it.
Cockpit + ADAS. One SoC family.
Snapdragon Ride for ADAS, Cockpit Elite for the cabin, and Ride Flex for both — with industry-leading power efficiency, integrated modem, and pin-compatibility across the family.
| Snapdragon Ride Flex | Cockpit + ADAS consolidation in a single SoC, scalable variants ~700 TOPS |
| Ride Elite (SA8775P / SA8797P) | Premium ADAS / AD SoC with NPU acceleration L2+ to L3 |
| Cockpit Elite Gen 4 | Class-leading multi-display cockpit SoC 6 displays |
| Power efficiency | Typically half the thermal footprint of comparable competitors Passive-cool capable |
| Integrated modem | 5G NR + C-V2X · OTA at scale connected-by-design |
OS support
Full stack QNX for safety-critical, Linux for general compute, Android Automotive for the consumer surface.
AI runtime
Quantization, on-device inference, and NPU offload. Strong ONNX and PyTorch import paths.
Sensor + perception
Sensor drivers, calibration, and reference perception pipelines tuned for the Hexagon NPU.
Cloud-based dev
Cloud-hosted target emulators for development and CI before silicon is available.
Ride is the right platform for cost-efficient cockpit + ADAS consolidation, programs with aggressive thermal targets, and OEMs that value the integrated modem and the consumer-grade software stack lineage. It's the volume platform of the next decade.
The platform that scales economically from luxury to volume.
Foundation models. World models. Policies.
The three classes of AI that, working together, define modern autonomy and cockpit — perception backbones, generative world models, and the policies that turn intent into action.
Perception, language, and shared representations.
BEV transformers
Large-scale pretraining on multi-camera, multi-sensor automotive data. Reusable backbones across perception, prediction, and planning heads.
Vision-language models
For HMI, scene-understanding narration, and as the language module of VLA policies. Compact on-device variants + cloud-scale fallback.
Speech & ambient
Multilingual ASR, intent classification, and ambient-sound understanding (emergency vehicles, glass-break, child cry).
Cross-modal representations
Joint embeddings that let the planner and the cockpit agent reason in the same conceptual space about the same scene.
Generative simulators of the physical world.
World models predict how a scene evolves under control inputs — the foundation of closed-loop simulation, rare-event synthesis, and the next generation of E2E autonomy.
| GAIA-2 (Wayve) | Controllable driving-video generation conditioned on actions and scenario tags Closed-loop sim |
| NVIDIA Cosmos | Physical-AI world foundation model family for robotics & AV simulation Open + commercial |
| DriveDreamer / GenAD | Research and emerging production world models for AV training Synthetic data |
| Use cases | Edge-case mining, closed-loop policy training, regression testing, scenario authoring Replace miles |
From modular to vision-language-action.
Rule-based + ML hybrid
The default for L2+ — learned components inside a deterministic shell. Mature certification path.
Trajectory networks
Networks predicting trajectories directly from BEV perception. Used as the planning head in UniAD-style stacks.
Vision-language-action
Foundation-model policies that take vision + language + intent and produce actions. The Wayve and Tesla FSD v12+ pattern.
RL fine-tuning
Reinforcement learning over world-model rollouts; reward modeling for comfort, safety, and naturalness.
The frontier of physical AI, productionized.
Agents in the cabin — and across the fleet.
The voice assistant is becoming an agent. So is the dispatch system. So is the predictive-maintenance loop. We design the agent layer that closes the gap between user intent and outcomes in the real, physical world.
Completes tasks. Doesn't just answer questions.
SLM + cloud LLM
On-device SLM for low-latency intent and offline operation, cloud LLM for complex reasoning, with smart fallback.
Vehicle & world tools
HVAC, nav, charging, calendar, smart-home, payments, and OTA — exposed as typed, sandboxed tools to the agent.
Per-occupant context
Profile memory, calendar awareness, route habits — privacy-aware and explicitly user-managed.
Multi-step task
"Charge to 80% on the way to the meeting, find a coffee place 5 min off the route, and message Sarah I'll be 10 min late."
Operational AI outside the cabin.
Robotaxi orchestration
Agentic dispatch: matching riders, optimizing routes, handling exceptions, surfacing the right thing to a human only when needed.
Tele-assist agents
Triage, prioritize, and resolve common edge cases automatically; escalate the complex ones to a human operator with full context.
Predictive agents
Fleet-wide health-monitoring agents that schedule maintenance, order parts, and route to depots — with cost-aware decisions.
Service agents
Owner-facing agents that handle routine service requests, warranty inquiries, and feature explanations — at brand-quality SLA.
Agents that fail safely, when they fail.
| Tool-use policy | Capability scoping, rate limits, confirmation flows for high-impact actions By-design |
| Output filtering | Hallucination detection, brand-voice enforcement, safety filters Multi-layer |
| Delegation lines | Clear boundary between agent suggestions and driver-confirmed actions Especially motion |
| Benchmarks | Scenario suite, jailbreak resistance, multi-turn task success Versioned |
| Telemetry | Anonymous task-success telemetry for continuous improvement Privacy-aware |
Agents that act — with the safety to do so.
From 100 ECUs to a few zones.
The shift from distributed-domain to zonal + central-HPC architectures is the single biggest cost, complexity, and innovation lever in modern vehicle programs. We help OEMs make it without breaking what already works.
Zonal + HPC, done pragmatically.
Central compute
1–2 high-performance compute units running ADAS, cockpit, and vehicle-domain workloads. Hypervisor-partitioned.
Zone controllers
4–6 zonal ECUs handling I/O aggregation, power distribution, and local actuation. Connected by 1–10G automotive Ethernet.
Smart sensors
Sensors with embedded processing where it adds value; raw streams where central fusion is preferred.
TSN Ethernet backbone
Time-sensitive networking with deterministic latency for safety traffic; best-effort for media and OTA.
| AUTOSAR Adaptive | Service-oriented architecture with ara::com, SOME/IP, persistency Production standard |
| DDS | Where latency and many-to-many publish-subscribe is needed Real-time |
| SOME/IP | Service discovery and RPC across the SOA fabric Mature |
| Classic AUTOSAR | Still the right tool for low-end ECUs and safety-critical real-time Coexistence |
| OTA | Differential, signed, multi-ECU updates with rollback UNECE R156 |
Zonal architectures reduce harness mass and cost, simplify supplier ecosystems, enable feature-on-demand business models, and — most importantly — let the vehicle improve materially after the customer drives off the lot. The vehicles that get this right will be the ones customers stay with for a decade.
Design the architecture once. Live with it for ten years.
The enterprise vertical.
Finance, People, GTM, Data, and the integration fabric that ties them together. We architect, implement, and run the systems that make modern enterprises operate — with the same engineering rigor we bring to vehicles.
Ten domains, one delivery org.
Enterprise transformation requires depth across the full technology landscape — and the discipline to operate it after go-live. Negits brings both.
Finance & Accounting
Anaplan, Apttus, Coupa, Concur, Zuora, BlackLine, Stripe, SAP, PayPal, Oracle, Workday Financials.
Enterprise Cloud & Integrations
ETL, Boomi, Informatica, SnapLogic, Fivetran, MuleSoft, Workato, Cleo, Talend, AWS, Azure, GCP, Oracle.
Application & Tech Stack
Full-stack, microservices, Node.js, React, Angular, Java, .NET, iOS, Android, mainframe, COBOL, RPG.
Data Processing
SQL, PowerBI, Tableau, Alteryx, Clarity, R, SAS, ETL, DWH, Terraform, Spark, Scala, Hadoop, Python.
HCM
Workday, ADP, BambooHR, Replicon, GreenHouse, Zoho, Intuit.
Sales, Marketing & CS
Salesforce, NetSuite, Marketo, Adaptive Insights, Slack, Gainsight, Zendesk, JSD.
DevOps & IT
Kubernetes, Docker, Ansible, JIRA, ServiceNow, DUO, Okta, Splunk, Atlassian, Snowflake, Slack, Trello.
Streaming Framework
Apache Kafka, Confluent, Spark Streaming, Flink, Apache Beam — for event-driven enterprise data flows.
Data Analytics & ML
Advanced statistical modeling (GLM, mixed effects) and machine learning (clustering, classifiers, neural networks).
Data Storage
Cloud services (AWS, S3, GCM, Azure), Snowflake, Redis, MySQL, Elasticsearch, Dropbox.
L1, L2, L3 — full lifecycle.
Service delivery includes development, enhancements, incidents, Ops, business engagement, BRD/FDD/TDD authoring, solution architecture, QA, UAT, go-live, and post-go-live support — with full delivery responsibility across project management, Agile operations, reporting, dashboards, SOX compliance, technical leadership, QA, release management, and IT.
Functional analysts
Business systems analysts, business users, functional architects translating business requirements into system designs.
Technical architects & leads
Solution architects, technical leads, senior developers driving design and implementation.
PM · QA · RM · SOX
Project management, QA leads, release managers, SOX compliance specialists ensuring auditable delivery.
The ES portfolio, connected.
Enterprise systems with the rigor of a vehicle program.
The ES portfolio in one picture.
Enterprise systems portfolios typically span Finance, GTM, People, Analytics, and Integration. We architect the connections — and the data and governance fabric that turns disconnected SaaS into a coherent operating platform.
Five domains. One integrated whole.
Order-to-Cash · Quote-to-Cash
O2C, Q2C, R2R, S2P, P2P process orchestration across finance and operations. Anchored on the ERP of record.
Planning & performance
Financial planning, budgeting, forecasting, consolidation — Anaplan, Adaptive Insights, Hyperion / Oracle EPM.
Customer systems
Salesforce, NetSuite, marketing automation, and customer success platforms unified through SOA.
Workday core
Workday HCM with Talent, Performance, Learning, Security, Reporting — and Payroll, Time, Absence on top.
EDW + analytics fabric
Enterprise data warehouse, BI tooling, data governance, and ETL / integration layer connecting all systems.
Automation · Splunk · eSign
Cross-cutting capabilities — RPA / automation, observability, contract signing — that touch every workflow.
| Service tiers | L1 helpdesk · L2 application support · L3 development & enhancements Full coverage |
| Project lifecycle | BRD · FDD · TDD · Solution architecture · QA · UAT · Go-live · PGL support End-to-end |
| Operating model | PM · Agile ops · reporting & dashboards · SOX compliance · QA · release management Full responsibility |
| Roles | Functional · technical · BSA · architects · leads · developers · QA · RM · SOX Mixed-discipline |
A coherent enterprise platform, not a SaaS zoo.
Finance systems — functional + technical.
Developers, production support, admins, SOX specialists, scrum masters, accountants, finance teams, and procurement specialists — Negits delivers the full Finance technology and operations capability.
OTC · PTP · RTR · IP · CLM.
Order-to-Cash
Quote, order, billing, collections, revenue recognition. Platforms: Adyen, Zuora, Salesforce CPQ.
Procure-to-Pay
Sourcing, contracts, requisition, PO, invoice, payment. Platforms: Coupa, Certa, Concur, Ironclad.
Record-to-Report
GL close, reconciliations, consolidations, reporting. Platforms: BlackLine, Avalara, Oracle, NetSuite.
Integrated Planning
Budgeting, forecasting, scenario modeling. Platforms: Anaplan, NetSuite, Oracle Financials.
Contract Lifecycle
Contract authoring, negotiation, execution, renewal. Platforms: Ironclad, Apttus, Conga.
Salesforce + tax
Salesforce as system-of-engagement layered with tax engines (Avalara, Vertex) and global compliance.
| Functional | Solution leads · BSAs · accountants · finance team partners · procurement specialists Domain-fluent |
| Technical | Developers · integrators · admins · prod support · automation engineers Hands-on |
| Governance | SOX compliance · audit liaison · controls testing · scrum & release management Auditor-ready |
| Platforms | Anaplan · Apttus · Coupa · Concur · Zuora · BlackLine · Stripe · SAP · Oracle · Workday Financials Multi-platform |
Close the books. Stay audit-ready.
People & Payroll portfolio.
Workday-centric HCM portfolio spanning Payroll, Hire-to-Retire (HTR), Talent, Performance, Time, and Absence — with global payroll integrations and a managed-service operating model.
WD US Payroll
Workday US Payroll configuration, tax updates, garnishments, off-cycle runs, year-end. Production support included.
WD US Benefits
Open enrollment, life events, carrier integrations, ACA compliance reporting.
WD Advanced Compensation
Merit, bonus, equity cycles. Compensation plan design and cycle execution.
CloudPay integrations
Global payroll via CloudPay (and partners) integrated to Workday for unified employee experience.
WD Core HCM
Organizational structure, supervisory orgs, job catalog, security model.
WD Global Time Off & Tracking
Global time off, leave administration, timekeeping with country-specific rules.
WD Talent & Performance
Goals, reviews, calibration, talent pools, succession planning, learning paths.
WD Reporting & PRISM
Workday Reporting, Calculated Fields, PRISM Analytics, and external BI integration.
| Service tiers | L1 employee helpdesk · L2 Workday admin · L3 development & integrations 24/5 or 24/7 |
| Roles | WD functional · technical · integration · reporting · payroll ops specialists Workday-certified |
| Operations | Weekly releases · semi-annual major releases · year-end · tenant management Lifecycle-managed |
Pay on time. Develop the workforce.
GTM — CPQ, sales, marketing, CS.
A unified go-to-market technology stack — from CPQ through sales execution, marketing, and customer success — with the data and process plumbing to make them work as one revenue engine.
Configure · Price · Quote
Product catalog, pricing rules, approval workflows, quote-to-order handoff. Platforms: Apttus, Salesforce CPQ.
Sales execution & legal
Salesforce, opportunity management, deal desk, commissions (Xactly), planning (Anaplan), legal workflows (OneTrust).
Demand & engagement
Marketo, Iterable, Drift, Segment CDP — campaign orchestration, lead lifecycle, and event tracking.
Customer success
Gainsight, Zendesk, Clarizen, SurveyMonkey, CSOD — health scoring, support, services delivery, learning.
| Sales platforms | Salesforce · Apttus · Xactly · Anaplan · Drift · OneTrust · Segment CDP Best-of-breed |
| Marketing | Marketo · Iterable · Adaptive Insights · GainSight Lifecycle |
| CS platforms | Gainsight · Zendesk · SurveyMonkey · Clarizen · CSOD Retention-grade |
| Integrations | SOA-style integration to Finance, HCM, and product systems via Boomi / MuleSoft Real-time |
From lead to renewal — one revenue engine.
Data, analytics, and ML.
From SQL and dashboards to advanced statistical modeling and machine learning — the analytics layer of the enterprise, designed to produce decisions, not just charts.
Data engineering
SQL, ETL pipelines, DWH, Spark, Scala, Hadoop, Python — modern and legacy data engineering stacks.
Business intelligence
PowerBI, Tableau, Alteryx, Clarity, R, SAS — analyst-grade tooling with governed datasets.
Cloud data infra
Terraform-managed cloud data platforms on AWS, Azure, GCP, Snowflake. CI/CD for pipelines.
Event-driven data
Apache Kafka, Confluent, Spark Streaming, Flink, Apache Beam for real-time enterprise data flows.
Storage tier
Cloud (AWS S3, GCM, Azure, Dropbox), Snowflake, Redis, MySQL, Elasticsearch — sized to workload.
Statistical & ML modeling
GLM, mixed effects, clustering, classifiers, neural networks. From experiment notebooks to production endpoints.
EDW with semantic layer · data quality · lineage · catalog · access controls. The discipline that turns analytics from a department into an operating asset.
Decisions per dashboard, not the other way around.
The integration fabric.
Modern enterprises run on dozens of SaaS systems. The integration fabric is what turns that into one operating platform — and it's where most transformations either succeed or quietly fail.
Boomi · MuleSoft · Workato
Service-oriented integration platforms for real-time API orchestration and event-driven workflows.
Informatica · SnapLogic · Talend
Batch and bulk ETL for data warehousing and analytics-grade pipelines.
Fivetran
Managed ELT for SaaS-to-warehouse data movement with automated schema management.
Cleo
EDI and partner-network integration for trading-partner data exchange.
| AWS | Compute, storage, data, ML, integration; landing zone & well-architected reviews Multi-account |
| Azure | Compute, data, AD, Power Platform; Microsoft-anchored enterprises M365-integrated |
| GCP | Data & ML-anchored workloads; BigQuery, Vertex AI, Dataflow Data-native |
| Oracle | OCI for Oracle-heavy estates; ERP-aligned cloud footprint ERP-anchored |
The fabric beneath the SaaS skyline.
DevOps & IT operations.
CI/CD, containers, observability, identity, and the developer experience that lets enterprise engineering teams actually ship.
Kubernetes · Docker
Container orchestration, Helm-managed deployments, service mesh, multi-cluster federation.
Ansible · Terraform
Infrastructure as code, configuration management, and policy-as-code at enterprise scale.
JIRA · ServiceNow
Service management, change control, incident response, and developer-friendly workflows.
Okta · DUO
Identity and access management, SSO, MFA, lifecycle management across enterprise apps.
Splunk · Snowflake
Logs, metrics, traces — and the data warehouse to power SRE, security, and business analytics.
Atlassian · Slack · Trello
Documentation, project boards, asynchronous communication, and developer-experience tooling.
Engineering speed, without losing control.
Dedicated PROD support desk.
A four-quadrant support model — Critical, Important, Monitor, Perform — with tiered service request handling, dedicated time-zone coverage, and weekend / after-hours availability. "Always On".
Critical support
L1 defects, integration outages, project go-lives, migration cutovers, upgrade incidents — handled with priority response.
IT & HRM
IT infrastructure monitoring, HRM platforms, identity, and core enterprise applications.
Application & data
L2 defects, application support, data support, integration monitoring, technical support.
Enhancement & vendor
Enhancement requests, vendor coordination, finance system tuning, continuous improvement work.
| Tier handling | Tiered Service Request handling (Run-The-Business model) Priority-aware |
| Coverage | Dedicated time-zone support with < 2% downtime target Follow-the-sun |
| Priority | Priority request handling with documented routing & escalation SLA-bound |
| Triage | First-level issue debugging & reporting at point-of-contact L1 enabled |
| Going extra mile | Weekend & out-of-support-hours coverage for critical events "Always On" |
The quiet team that keeps the business running.
Generative AI, agents, and physical AI.
A horizontal practice serving both verticals — generative AI, LLMs, retrieval-augmented generation, Model Context Protocol integrations, and agentic systems. Same architectural rigor across in-vehicle agents and enterprise-grade copilots.
One stack. Two domains.
Generative AI
Text, image, audio, and code generation embedded into vehicle UX and enterprise workflows. Strategy, build, deploy, and operate.
LLMs & SLMs
Frontier-model selection, fine-tuning, distillation to small models, on-device deployment, evaluation, and cost optimization.
RAG
Retrieval-augmented generation against enterprise knowledge — embeddings, vector stores, hybrid search, and grounding.
MCP
Model Context Protocol servers exposing enterprise systems and vehicle data as typed, sandboxed tools for AI agents.
Agentic AI
Multi-step task-completing agents — in the cabin, in the cockpit, in customer service, in operations.
Foundation & World Models
Vision-language-action models, world models for closed-loop simulation, physical-AI policies for vehicles and robots.
AI everywhere we deliver.
The AI practice isn't a side bet — it's woven through every vertical we serve. In Automotive: foundation-model perception, in-cabin agents, world-model validation. In Enterprise: copilots in finance, GTM, and HR; RAG over institutional knowledge; agentic ops over ticketing and incident response.
From tokens to action.
One AI strategy. Two verticals' worth of impact.
Generative AI.
From experiments to production: strategy, model selection, build, deploy, observe, and govern. Generative AI that survives contact with real users, real workflows, and real procurement.
In-cabin assistants
Conversational HMI, owner's-manual Q&A, multi-step task completion, route & charging planning agents.
Engineering productivity
Test-case generation, scenario authoring, code-review copilots for vehicle software, design-doc drafting.
Finance & ops copilots
Variance analysis, journal-entry suggestions, audit-trail explanations, contract summarization.
GTM acceleration
Sales prospecting, account research, proposal drafting, customer-success summarization across calls and emails.
People & HR
Policy Q&A, onboarding copilots, performance-cycle assistance, knowledge-search across HCM data.
Multimodal generation
Text, image, audio, code, and structured-data generation pipelines with brand-voice and safety controls.
| Discovery | Use-case shortlist, ROI sizing, build-vs-buy decisions, risk & governance scoping 2–4 weeks |
| Build | Model selection, prompt & eval harness, RAG / agent architecture, integration to systems-of-record 8–16 weeks |
| Operate | Observability, eval drift, cost & latency tuning, prompt versioning, safety monitoring Ongoing |
| Govern | Policy, data classification, DLP, audit trails, model-risk management aligned with NIST AI RMF Auditor-ready |
From demo to deployed. With governance.
LLMs and small language models.
Frontier model selection, fine-tuning, distillation, on-device deployment, evaluation, and cost optimization — across cloud-hosted LLMs and edge-deployed SLMs in vehicles and devices.
Cloud LLMs
Claude (Anthropic), GPT (OpenAI), Gemini (Google), Llama, Mistral — selection matched to task, cost, latency, and data residency.
On-device small models
3B–8B parameter models distilled for on-device deployment in vehicles and edge devices. Sub-second latency, offline-capable.
Adaptation
LoRA / QLoRA fine-tuning on proprietary data. Domain-specific adaptation without losing base-model capability.
Cloud-to-edge distillation
Knowledge distillation from frontier models into small task-specific models for cost & latency.
Evaluation harness
Task-specific benchmarks, golden sets, regression suites, A/B routing — with continuous evaluation in production.
Optimization
Routing between models by request difficulty, prompt caching, batching, and tiered-model strategies — material cost savings.
| Cloud LLM | Complex reasoning, multi-step planning, long-context tasks, agent orchestration Best capability |
| On-device SLM | Low-latency intent classification, wake-word, on-device drafting, offline operation Best latency |
| Hybrid | Intent on-device, fallback to cloud LLM for complex queries — the production default Best balance |
| Fine-tuned mid-size | Repetitive domain-specific tasks at scale — often the best cost-per-quality point Best economics |
The right model for the right job.
Retrieval-augmented generation.
Ground LLMs in your enterprise knowledge — policies, contracts, runbooks, manuals, ticket history, code, design docs. Retrieval-augmented generation that's accurate, attributable, and access-controlled.
Source connectors
Connectors to SharePoint, Confluence, Notion, Google Drive, Salesforce, Workday, Jira, ServiceNow, S3, code repos.
Chunking & enrichment
Semantic chunking, structure-preserving parsing, metadata enrichment, summarization for retrieval.
Embeddings
OpenAI, Cohere, BGE, or self-hosted embedding models. Per-tenant and per-domain embedding strategies.
Vector + hybrid
Pinecone, Weaviate, Qdrant, pgvector, Elasticsearch with vector. Hybrid keyword + semantic search.
Re-rank & ground
Multi-stage retrieval, cross-encoder re-ranking, citation extraction, hallucination detection.
Access controls
Per-user permissions at retrieval time, source-system ACL propagation, audit trails, PII redaction.
| Golden sets | Curated question-answer pairs with cited sources, used for regression testing Per-domain |
| Faithfulness | Hallucination detection, citation enforcement, abstain-when-uncertain protocols > 95% target |
| Retrieval metrics | nDCG, MRR, recall@k — measured continuously, alerted on drift Observability |
| User feedback | Thumbs / structured feedback feeding re-rank and re-training loops Closed-loop |
Answers your auditor would accept.
Model Context Protocol.
MCP turns enterprise systems and vehicle subsystems into typed, sandboxed tools that any compliant AI agent can use safely. The protocol that's becoming the connective tissue of agentic AI.
Enterprise system exposure
MCP servers for Salesforce, Workday, NetSuite, Jira, ServiceNow, Slack, Snowflake, internal APIs — turning them into agent-callable tools.
Vehicle & cockpit
MCP servers exposing vehicle telematics, charging, navigation, HVAC, and OTA functions to cabin agents safely.
Tool registry & governance
Centralized catalog of MCP tools across the enterprise with permissions, rate limits, and audit logging.
Agent & copilot clients
MCP-aware agent runtimes that discover, invoke, and chain MCP tools to complete multi-step tasks.
Sandboxed execution
Capability-scoped tool access, per-user permissions, output filtering, and confirmation flows for high-impact actions.
Tool-use evaluation
Benchmarks for tool-selection accuracy, parameter correctness, multi-step success — measured continuously.
Before MCP, every agent needed bespoke glue code to every system. With MCP, an agent that "speaks MCP" can use any tool that exposes an MCP server — and an enterprise that exposes its systems via MCP can switch agent vendors without rewriting integrations. It's the IT-architecture decision that determines how much agent value you'll actually capture.
The integration layer of the agentic enterprise.
Agentic AI.
Agents that complete tasks, not just answer questions. From cabin agents in vehicles to operations agents in the enterprise — designed for safety, governance, and real outcomes.
In-vehicle agents
Voice + multimodal cabin agents that complete tasks — route, charge, navigate, message, control vehicle, brief autonomy stack.
Customer-facing agents
Owner-facing service agents, sales prospecting agents, customer-success agents handling routine cases at brand-quality SLA.
Internal copilots
Finance close agents, HR query agents, IT helpdesk agents, sales-ops agents — completing back-office work autonomously.
Engineering agents
Code-generation, code-review, test-authoring, and incident-triage agents wired into the developer workflow.
Operational agents
Dispatch, remote-assist triage, predictive-maintenance scheduling — agentic decisions over fleet ops.
Analyst & research
Multi-step research agents pulling from multiple sources, synthesizing, and producing decision-ready briefs.
| Runtime | Frontier LLM orchestration + on-device SLMs for fast paths · MCP-aware tool use Hybrid |
| Memory | Per-user, per-session, and shared knowledge memory with retention policy & user control Privacy-aware |
| Planning | Multi-step task decomposition, sub-agent delegation, error recovery, human handoff Recursive |
| Guardrails | Tool-use policy · output filtering · confirmation flows · sandboxed execution Multi-layer |
| Eval | Scenario benchmarks · jailbreak resistance · multi-turn task success · production telemetry Continuous |
| Compliance | NIST AI RMF · EU AI Act readiness · SOC 2 audit trails · regulated-industry controls Auditable |
We don't build "an agent" — we build the agent platform. Tool registry (MCP), evaluation harness, observability, guardrail layer, and the agent runtime itself. Then we ship two or three high-value agents on top of it as the proof — and let your team scale agents from there.
Agents that act, with the safety to do so.
Pre-built. Production-ready.
Modular building blocks that compress months of integration work. Each product ships with a reference design, validation suite, safety case template, and SoC porting guide.
NEGITS DRIVE
Full-stack ADAS / AD reference platform
A production-grade autonomy stack delivering L2+ on launch and an upgrade path to L3/L4. SoC-agnostic, configurable sensor sets, and tuned reference models for highway and urban ODDs.
- Modular and hybrid-E2E variants
- NVIDIA DRIVE & Qualcomm Ride reference ports
- ISO 26262 ASIL D safety case scaffolding
- HD-map and mapless modes
- Cloud training & simulation pipeline included
NEGITS CABIN OS
Single-SoC cockpit reference platform
Cluster, IVI, HUD, and rear-seat consolidated on one SoC under a QNX or Wind River hypervisor, with native Android Automotive guest and full multi-display compositor.
- Up to 6 displays, hypervisor-isolated
- Reference UX kit with adaptive themes
- Multimodal voice + gaze + gesture stack
- App framework with sandboxed extensions
- OTA, telemetry, and remote-tuning baked in
BEV·FUSE
Multi-sensor BEV perception module
A drop-in BEV transformer-based perception stack supporting camera, imaging radar, and lidar fusion with temporal attention and a unified occupancy + object output.
- Configurable BEVFormer / BEVFusion backbones
- Lane graph and occupancy in one head
- Pre-trained checkpoints + fine-tune pipeline
- Quantization-aware export to TensorRT / QNN
PLANCORE
Hierarchical planner and controller
Behavior-layer + motion-planner + NMPC controller with a safety supervisor and hot-swappable cost functions for highway, urban, and parking ODDs.
- RSS-style safety envelope
- Minimum-risk maneuver library
- Hand-tunable behavior parameters
- Sub-100 ms decision cycles
SENTINEL DMS / OMS
Cabin monitoring suite
Driver and occupant monitoring meeting EU GSR-2 and Euro NCAP 2026 requirements. NIR camera, radar CPD, and ToF fusion with on-device inference.
- Drowsiness, distraction, gaze, emotion
- Child presence detection (radar-based)
- Seat-belt and occupant classification
- Regulatory test reports included
NEGITS AGENT FRAMEWORK
In-cabin agentic AI runtime
An on-device + cloud agent runtime with tool registry, memory store, guardrails, and evaluation harness — purpose-built for vehicles and the safety envelope they live in.
- SLM-on-device + cloud-LLM orchestration
- Vehicle tool registry (HVAC, nav, charge, OTA)
- Multi-occupant memory and profiles
- Scenario-based agent benchmarks
LOOPYARD
Closed-loop simulation & data flywheel
Scenario authoring, world-model-driven synthetic data, replay simulation, and a labeling-to-retraining pipeline. Designed to scale from a single workstation to a multi-cluster cloud.
- CARLA + Cosmos + custom integrations
- Edge-case mining from fleet telemetry
- Auto-labeling with foundation models
- Regression suites tied to safety case
SAFETYKIT
ISO 26262 + SOTIF tooling and templates
HARA, ASIL decomposition, FTA / FMEDA, SOTIF triggering-condition analysis, and full safety-case templates aligned with type approval requirements.
- Tool-qualified by domain (TCL 1 / 2 / 3)
- UNECE R155 / R156 cybersecurity bundle
- Auditor-ready artifact pack
- OEM-tailored gating checklists
License a product, port it to your SoC, or have us deliver to SOP.
Negits Drive.
Full-stack ADAS / AD reference platform delivering L2+ on launch and an upgrade path to L3 and L4. SoC-agnostic, configurable sensor sets, tuned reference models for highway and urban ODDs.
Production BEV stack
BEVFormer / BEVFusion backbones with occupancy and lane-graph heads. Pre-trained checkpoints and a fine-tune pipeline.
Hierarchical planner
Behavior + motion + NMPC controller with RSS-style safety envelope and a fallback minimum-risk-maneuver library.
ASIL D scaffolding
HARA, FMEDA, FTA artifacts, and a safety supervisor independent of the main perception channel.
LoopYard hooks
Out-of-the-box closed-loop sim, replay, and regression suite tied to release gating.
| SAE level | L2+ at launch · L3 highway upgrade path · L4 urban variant Configurable |
| SoC support | NVIDIA DRIVE Thor / Orin · Qualcomm Ride Flex / Elite · TI / Mobileye on request Multi-target |
| Sensor sets | Reference configs from camera-radar L2+ through full L4 with lidar & thermal Sized by ODD |
| Safety | ISO 26262 ASIL D for the safety supervisor; ASIL B for nominal channels Type-approval ready |
| Delivery | Source + reference design + safety case template + porting guide Licensed |
License it. Port it. Or have us deliver to SOP.
Negits Cabin OS.
A single-SoC cockpit reference platform: cluster, IVI, HUD, and rear-seat consolidated under a QNX or Wind River hypervisor, with native Android Automotive guest and a full multi-display compositor.
Up to 6 surfaces
Cluster, central IVI, passenger display, HUD, and rear-seat — composited from one SoC with hypervisor isolation.
Adaptive themes
Reference UX with brand-themable design tokens, dark/light schemes, accessibility-first typography.
Multimodal stack
On-device wake + ASR, cloud LLM intent, voice + gaze + gesture orchestration out of the box.
Sandboxed apps
App framework for OEM-curated extensions with capability-scoped APIs and signed delivery.
| SoC support | Qualcomm Cockpit Elite · Ride Flex · NVIDIA Thor · TI TDA4VH (cost tier) Multi-target |
| Hypervisor | QNX Hypervisor (default safety) · Wind River Helix · COQOS · Xen Type-1 |
| Guest OS | QNX (cluster, ASIL B) · AAOS (IVI) · Linux (services) · safety-RTOS supervisor 3–5 guests |
| OTA & telemetry | Differential, signed, multi-ECU updates with rollback; opt-in analytics UNECE R156 |
Differentiate the brand where customers live every day.
BEV·Fuse.
A drop-in BEV transformer perception module fusing camera, imaging radar, and lidar with temporal attention and a unified occupancy + object output head.
BEVFormer / BEVFusion
Configurable backbones tuned for production constraints. Modality-agnostic fusion in BEV space with learned cross-attention.
Multi-task output
Detection, tracking, lane graph, free-space, 3D occupancy, traffic-light state — all from one forward pass.
4-frame attention
Temporal self-attention for velocity, occlusion handling, and stable tracking across frames.
QAT to INT8 / FP8
Quantization-aware training preserves > 98% accuracy. Pre-built exports for TensorRT, QNN, OpenVINO, SNPE.
| Latency | 30 ms on DRIVE Thor · 50 ms on Qualcomm Ride · deterministic batches 10 Hz cycle |
| Detection | mAP and NDS competitive with published BEVFormer / BEVFusion benchmarks nuScenes-tested |
| Lane graph | Vectorized centerlines + topology to 100 m horizon Online HD-map |
| Robustness | Sensor-failure-aware fusion; covariance drops with sensor health Graceful degrade |
Perception is the load-bearing wall. We harden it.
PlanCore.
Hierarchical planner and controller — behavior layer, NMPC motion planner, and a safety supervisor with hot-swappable cost functions for highway, urban, and parking ODDs.
Tactical layer
Lane selection, gap acceptance, merge intent, intersection negotiation with 3–10 second horizon.
NMPC optimization
Sample-based + optimization-based hybrid using IPOPT / OSQP. Soft and hard constraints under comfort budgets.
200–500 Hz tracking
Lateral MPC with curvature feedforward; longitudinal PID with jerk-limited shaping. Actuator-aware.
ASIL D safety
RSS envelope, fallback planner, minimum-risk maneuver library. Independent of nominal channel.
| Decision rate | Motion 100 Hz · control 200–500 Hz · behavior 10–20 Hz Hard real-time |
| Comfort budget | Configurable jerk, lateral accel, angular rate; ISO 2631 weighted < 2.5 m/s³ |
| ODDs | Highway · urban · parking · trained-path summon profiles included Hot-swappable |
| Tuning | Hand-tunable behavior parameters plus learned-policy override hooks Hybrid |
The seam where most stacks show their weakness.
Sentinel. The cabin awareness suite.
Driver and occupant monitoring meeting EU GSR-2 and Euro NCAP 2026 requirements — NIR camera, radar child-presence detection, and ToF fused with on-device inference.
Drowsiness · distraction · gaze
PERCLOS, blink rate, head-pose, gaze-zone classification. Phone-in-hand and impairment-pattern detection.
Occupant classification
Per-seat presence, class (adult / child / none), seat-belt compliance, posture and motion.
Child presence (radar)
EU GSR-2 mandated unattended-child detection through blankets and car-seats.
Affective optional
Wellness and cabin-adaptation cues — opt-in, privacy-controlled, on-device only.
| Latency | < 100 ms drowsiness alert · < 50 ms gaze classification On-device NPU |
| Regulatory | EU GSR-2 · Euro NCAP 2026 · C-NCAP · UNECE R152 Test-ready |
| Sensors | NIR 940 nm camera · optional ToF · 60/77 GHz radar for CPD Pillar or RVM mount |
| Privacy | No cloud round-trip for safety functions; no recording by default GDPR-aware |
Compliant. And the experience customers don't hate.
Negits Agent Framework.
An on-device + cloud agent runtime with tool registry, memory store, guardrails, and an evaluation harness — purpose-built for vehicles and the safety envelope they live in.
SLM + cloud LLM
On-device SLM for low-latency intent and offline operation; cloud LLM orchestration for complex multi-turn reasoning.
Vehicle tool registry
HVAC, navigation, charge, OTA, calendar, smart-home, payment — exposed as typed, sandboxed tools.
Multi-occupant context
Per-driver profiles, calendar awareness, routine learning — privacy-aware and explicitly user-managed.
Policy & eval
Tool-use policy, output filtering, multi-layer hallucination defense, scenario benchmark suite.
| In-cabin | Multi-step task completion: charge planning, calendar nudges, smart-home control Voice + touch |
| Drive-link | "Route home avoiding tolls, find a charger I'll reach with 15%" — briefs the autonomy stack Goal → intent |
| Fleet ops | Dispatch, remote assistance, predictive maintenance for commercial fleets Operational |
| Customer service | Owner-facing service agents handling warranty, features, scheduling Brand-quality |
Agents that act, with the safety to do so.
LoopYard.
Closed-loop simulation, world-model-driven synthetic data, scenario authoring, and a labeling-to-retraining pipeline — designed to scale from a single workstation to a multi-cluster cloud.
OpenSCENARIO authoring
Library of regulatory and edge-case scenarios with parametric variation. Compatible with OpenSCENARIO 2.0.
CARLA + Cosmos + custom
Photoreal sim from CARLA and NVIDIA Cosmos plus deterministic kinematic sim for regression at scale.
Mining & auto-label
Edge-case mining from fleet telemetry, foundation-model-assisted auto-labeling, human-in-the-loop review.
Release-gate suites
Continuous regression tied to safety-case acceptance criteria. Build-gating against perception & planning KPIs.
| Throughput | Distributed sim across H100/H200 clusters; faster-than-real-time deterministic 10–100× wall-clock |
| Storage | Petabyte-scale fleet-data lake with semantic indexing Object-store native |
| World models | Cosmos integration for controllable rare-event generation Synthetic data |
| Integration | Drop-in for Negits Drive; SDK for third-party stacks CI-friendly |
Replace miles. Not safety.
SafetyKit.
ISO 26262 + SOTIF tooling, templates, and process — audit-survivable, OEM-tailored, and built into engineering rather than bolted on at the end.
HARA → safety case
Hazard analysis, ASIL decomposition, FMEDA, FTA, and a safety-case template aligned with type approval.
Triggering-condition library
3000+ cataloged triggering conditions, acceptance criteria templates, and a Bayesian release-gate framework.
R155 / R156 bundle
CSMS and SUMS templates, HSM integration guidance, intrusion-detection reference pipelines.
TCL 1 / 2 / 3
Tool-qualification packages for tools in the safety-critical pipeline. Pre-qualified where possible.
| Format | Templates + tooling + per-OEM tailoring workshop Hybrid |
| Audit support | Pre-audit dry-run, gap analysis, auditor-ready artifact pack Hands-on |
| Integration | Designed to slot into your existing PLM and ALM systems JAMA · Polarion · Codebeamer |
| Scope | L2 ADAS through L4 — passenger, commercial, off-highway All domains |
An auditor we'd welcome, not endure.
From strategy
to start-of-production.
Executive-level advisory paired with hands-on engineering. We don't write decks and leave — we ship code, sign off safety cases, and stay through SOP.
Autonomy & cockpit roadmap
Three- to ten-year program strategy: ODD definition, feature ladders, SoC partner selection, build-vs-buy decisions, P&L modeling, and competitive positioning against Tesla, Wayve, Mobileye, Huawei, Bosch, ZF, Aptiv, and the rest.
E/E and SDV architecture design
Zonal vs domain, HPC consolidation strategy, network topology, AUTOSAR Adaptive deployment, hypervisor and OS choice, and full safety-aware mapping of functions to hardware.
Technical & commercial due diligence
For investors, acquirers, and OEM partnerships — deep technical assessment of autonomy stacks, IP, talent, regulatory exposure, and competitive moat. We've evaluated startups, scale-ups, and joint-venture candidates.
Embedded engineering teams
Senior engineers and architects who plug into your program and deliver — perception model improvements, planner re-architecture, cockpit feature builds, validation infrastructure. Output is committed code, not PowerPoint.
ISO 26262 & SOTIF programs
Hazard analysis, ASIL decomposition, safety-case authoring, SOTIF triggering-condition analysis, tool qualification, and homologation support. Practical, audit-survivable, OEM-tailored.
APQP / PPAP / SOP
The unglamorous work that ships product: supplier qualification, line-side integration, PPAP submission, run-at-rate, and SOP gating. We've taken systems from prototype to series at multiple Tier-1s.
Org & talent strategy
For VP/CTO clients building autonomy or cockpit orgs from scratch — operating model design, role architecture, hiring strategy, technical interviewing, and interim engineering leadership.
VP- and CTO-level coaching
1:1 coaching for technical executives navigating autonomy programs, board reporting, OEM negotiation, and the political reality of multi-billion-dollar mobility bets.
A second opinion you'll actually respect.
Autonomy & cockpit roadmap.
Three- to ten-year program strategy: ODD definition, feature ladders, SoC partner selection, build-vs-buy decisions, P&L modeling, and competitive positioning.
Competitive intelligence
Deep benchmark against Tesla, Wayve, Mobileye, Huawei, Bosch, ZF, Aptiv, Momenta, Li Auto, XPENG and the rest. By geography and by tier.
Feature ladder
Year-by-year feature roadmap with NCAP scoring impact, willingness-to-pay analysis, and competitor matching.
Make / buy / partner
Per-component decisions on internal build, supplier outsourcing, JV, or M&A — with sequenced execution plan.
Investment case
Full cost model: BOM, software licensing, ML/cloud infra, data flywheel, validation, and revenue/TAM.
| Format | 6–12 week engagement with executive sponsor and working-team sessions Mixed remote / on-site |
| Deliverable | Board-ready strategy deck + execution plan + investment case CEO / CTO grade |
| Team | Partner-level lead + 2–3 senior consultants with domain expertise Hands-on |
The strategy work that survives the first OEM RFQ.
E/E & SDV architecture.
Zonal vs domain, HPC consolidation strategy, network topology, AUTOSAR Adaptive deployment, hypervisor and OS choice, and full safety-aware mapping of functions to hardware.
HPC + zonal design
Compute consolidation strategy, ECU rationalization, harness optimization, and TSN Ethernet backbone design.
SOA design
AUTOSAR Adaptive, SOME/IP, DDS deployment with service catalogs, lifecycle, and persistency.
Compute mapping
SoC selection (NVIDIA / Qualcomm / TI / Renesas / Mobileye) with workload-to-compute mapping.
ASIL allocation
Function-to-element ASIL allocation, decomposition strategy, and freedom-from-interference proof.
| Format | 8–16 weeks with embedded architects in your team Hands-on |
| Deliverable | Architecture spec + BOM + risk register + decision log Engineering-grade |
Architecture is a 10-year decision. Make it once.
Technical & commercial DD.
For investors, acquirers, and OEM partnership teams — independent assessment of autonomy stacks, IP, talent, regulatory exposure, and competitive moat.
Stack depth review
Code-level review of perception, planning, and validation. Real assessment, not vendor brochure summarization.
Patent & IP audit
Freedom-to-operate, IP ownership chain, open-source compliance review.
Org & people
Key-person dependency, engineering velocity, hiring trajectory, retention risk.
Compliance posture
ISO 26262, SOTIF, UNECE R155/R156, NHTSA, type-approval readiness by market.
| Format | 2–6 weeks · confidential · NDA-bounded Discreet |
| Deliverable | DD report + risk matrix + readiness scoring + recommended actions Investor-grade |
A second opinion the partners actually read.
Embedded engineering teams.
Senior engineers and architects who plug into your program and ship — perception model improvements, planner re-architecture, cockpit feature builds, validation infrastructure. Output is committed code, not PowerPoint.
BEV / fusion specialists
Senior ML and perception engineers for backbone improvements, head additions, and quantization to silicon.
Planner architects
NMPC, behavior, and learned-planner specialists for L2+ to L4 program needs.
SoC & middleware
QNX, AUTOSAR Adaptive, hypervisor, and SoC-specific runtime engineers.
Sim & data infra
Closed-loop sim, scenario authoring, data pipeline, and regression-suite engineers.
| Format | 3–18 months · embedded in your team or working as a feature pod Source-shipping |
| Handover | Documented code + runbooks + training of receiving team No vendor lock |
Senior engineers. Shipping. With your team.
ISO 26262 & SOTIF programs.
Hazard analysis, ASIL decomposition, safety-case authoring, SOTIF triggering-condition analysis, tool qualification, and homologation support. Practical, audit-survivable, OEM-tailored.
HARA & concept
Item definition, HARA, safety goals, functional safety concept. We start from your vehicle architecture, not a template.
Allocation & decomposition
ASIL decomposition, technical safety requirements, FMEDA, FTA — with measurable diagnostic coverage targets.
SOTIF + validation
Triggering condition catalog, acceptance criteria, validation campaigns, residual-risk justification.
Safety case + audit
Full safety case authoring, auditor dry-run, type-approval support across jurisdictions.
| Format | 12–24 month programs aligned to development phase gates Full lifecycle |
| Deliverable | Approved safety case + tool-qualified pipeline + auditor-ready artifacts Type-approval ready |
Safety as engineering rigor, not paper compliance.
APQP · PPAP · SOP.
The unglamorous work that ships product: supplier qualification, line-side integration, PPAP submission, run-at-rate, and SOP gating. We've taken systems from prototype to series at multiple Tier-1s.
Advanced product quality planning
5-phase APQP gating with quality, manufacturing, supplier, and validation milestones synchronized.
Submission package
All 18 elements of PPAP authoring and OEM submission — with experienced PPAP engineers.
Qualification & audit
Sensor, SoC, harness, and software-supplier qualification audits and process maturity assessments.
Run-at-rate to series
Pilot, run-at-rate, ramp, and series-production stabilization with measurable PPM and DPPM gates.
| Format | Program-aligned · embedded with your APQP team and on-site at plant Hands-on |
| Deliverable | SOP-ready system + PPAP submitted & approved + supplier matrix qualified Series-ready |
Prototype to start-of-production. With dollar-quantified milestones.
Org & talent strategy.
For VP/CTO clients building autonomy or cockpit orgs from scratch — operating model, role architecture, hiring strategy, technical interviewing, and interim engineering leadership.
Engineering org design
Functional vs platform, geographic, and ownership-line decisions. RACI, decision-rights, and operating cadences.
Strategy + execution
Role architecture, leveling, compensation benchmarks, sourcing strategy, and interview-loop design.
Domain-grade screens
Interview rubrics and screens for AV/cockpit roles — perception, planning, platform, safety, ML infra.
Bridge roles
VP- and director-level interim leadership while the permanent hire is being recruited.
| Format | 4–12 weeks for design; ongoing for interim leadership Confidential |
| Deliverable | Org design + hiring plan + interview loops + interim coverage CTO-grade |
Hire the right team. Once.
VP- and CTO-level coaching.
Confidential 1:1 coaching for technical executives navigating autonomy programs, board reporting, OEM negotiation, and the political reality of multi-billion-dollar mobility bets.
Reporting & influence
Framing autonomy programs for board and investor audiences. Risk framing. Milestone communication.
OEM & supplier
Tier-1 / OEM commercial framing, SoC partner negotiation, JV structuring.
High-stakes calls
Build-vs-buy, architecture choices, hiring decisions — confidential thinking partnership.
Cross-functional
Navigating the matrix between engineering, product, design, manufacturing, and finance.
| Format | Retainer · bi-weekly or monthly · async + scheduled sessions Confidential |
| Outcome | Clearer thinking. Better decisions. Less isolation at the top. Long-term |
The role is lonely. The decisions don't have to be.
Engineered for your
vehicle, your fleet,
your industry.
Reference solutions across passenger, commercial, off-highway, and robotics — each combining the right products, the right architecture, and an SOP-ready delivery plan.
L2+ NoP and HWA for a premium ICE/BEV platform
Camera-radar fusion on Qualcomm Ride with optional imaging-radar upgrade. Lane-change automation, navigate-on-pilot on mapped highways, and a memory-parking package. Engineered for cost-competitive silicon with a clear migration path to L3.
PRODUCTS · NEGITS DRIVE · BEV·FUSE · PLANCORE · SAFETYKIT
L3 highway pilot on a flagship sedan
Lidar-augmented sensor set on NVIDIA DRIVE Thor. Eyes-off operation under UNECE R157 with hand-back protocols, MRM, and a fully ASIL D safety supervisor. Includes type-approval support and OEM-tailored safety case.
PRODUCTS · NEGITS DRIVE · PLANCORE · SAFETYKIT · LOOPYARD
Single-SoC consolidated cockpit + ADAS
Qualcomm Ride Flex or NVIDIA Thor running cluster, IVI, HUD, rear-seat, DMS/OMS, and an L2+ ADAS partition under QNX Hypervisor. Materially reduces cockpit + ADAS hardware footprint and cuts ECU count by half.
PRODUCTS · CABIN OS · NEGITS DRIVE · SENTINEL · AGENT FRAMEWORK
L4 highway autonomy for Class 8 trucks
Long-range imaging radar and 1550 nm lidar, redundant compute, fail-operational architecture, and a hub-to-hub operational model with remote assistance. Tuned for U.S. interstate and EU TEN-T corridors.
PRODUCTS · NEGITS DRIVE (L4) · LOOPYARD · SAFETYKIT
Urban driverless platform with fleet ops
Full L4 urban stack with HD maps, V2X integration, world-model-based simulation, and a remote-operations console. Includes the agent layer for rider interaction and exception handling.
PRODUCTS · NEGITS DRIVE · AGENT FRAMEWORK · LOOPYARD · SAFETYKIT
Autonomous mining haul truck
Geofenced L4 operation on private haul roads with cm-grade GNSS-INS, redundant perception, and integration with mine dispatch systems. Operates 24/7 in dust, low-light, and extreme temperatures.
PRODUCTS · NEGITS DRIVE (rugged) · LOOPYARD · SAFETYKIT
Mobile robot autonomy for warehouse & yard
Adapted autonomy stack for AMRs and yard-tractors: VSLAM, multi-camera + radar, and a VLA policy for human-rich environments. Same core platform as the AV stack, tuned for slower speeds and tighter spaces.
PRODUCTS · NEGITS DRIVE (robotics edition) · BEV·FUSE
Modular autonomy IP for OEM RFQs
White-label autonomy and cockpit IP that Tier-1s can configure and quote into OEM programs. Includes pre-configured BOM templates, safety case scaffolding, and SoC-port matrices for fast RFQ response.
PRODUCTS · Full Negits stack · OEM-branding kit
Tell us the program. We'll show you the solution.
For the passenger car program.
From entry-tier L2+ to flagship L3 highway pilot, plus consolidated cockpit + ADAS on a single SoC — solutions tuned for the commercial reality of passenger-vehicle programs.
NoP on Qualcomm Ride
Camera-radar fusion with NoP and memory-parking. Cost-competitive silicon. Concept to SOP in 24 months.
Urban NoP with lidar
Lidar-augmented urban pilot on DRIVE Orin or Ride Elite. Highway + dense urban + memory parking.
Eyes-off highway pilot
Lidar-augmented L3 on DRIVE Thor. UNECE R157 type approval. Full handback protocols.
Cockpit + ADAS · 1 SoC
Ride Flex or DRIVE Thor running cluster, IVI, HUD, DMS/OMS, and L2+ — materially reduced hardware footprint and 50% fewer ECUs.
| L2+ scope | Sensors, compute, harness sized for volume programs Volume tier |
| L3 scope | Redundant compute & lidar sized for flagship programs Flagship tier |
| Concept-to-SOP | 24–36 months depending on platform reuse & supplier maturity Typical |
| NCAP target | 5-star Euro NCAP + 5-star C-NCAP achievable across the lineup Tuned for protocol |
Tell us the platform. We'll scope the program.
For Class 8 and the hub-to-hub future.
L4 highway autonomy for commercial Class 8 trucks with long-range sensing, redundant compute, fail-operational architecture, and a hub-to-hub operational model with remote assistance.
Long-range first
1550 nm long-range lidar, 300+ m imaging radar, multi-camera with extended-FOV. Range > passenger by 2–3×.
Redundant fail-operational
Dual-channel compute with cross-monitoring. Power-loss tolerance and graceful degradation.
Articulated-vehicle planner
Trailer-aware planning, articulated dynamics in the controller, load-aware comfort budgets.
Hub-to-hub model
Geofenced interstate operation with manned first-mile / last-mile and remote-assist for exceptions.
| System scope | Long-range sensing, redundant compute, fail-operational architecture Premium tier |
| ODD | Interstate / EU TEN-T corridors · daylight + night · most weather Configurable |
| Driver-out target | True L4 within geofence; remote-assist for narrow exception classes Phased |
The freight industry's most consequential productivity unlock.
Urban L4. Geofenced. Operational.
Full L4 urban autonomy with HD maps, V2X, world-model-based simulation, and a remote-operations console. Plus the agent layer for rider interaction and exception handling.
L4 urban autonomy
Premium sensor set, lidar-augmented BEV, HD-map-anchored localization, full driverless operation.
Tele-assist console
Triage UI, agent-assisted exception handling, secure low-latency video links.
In-vehicle agent
Voice + display agent for pickup, navigation context, support requests, and lost-and-found.
Ops orchestration
Dispatch, charging, depot routing, predictive maintenance — agentic where it helps.
| ODD | Geofenced urban polygons · weather-bounded · day + night Phased expansion |
| Coverage | 24/7 with depot-charging integration; remote-assist on call High utilization |
| Vehicle | OEM-partner platform or purpose-built · sensor-set agnostic Flexible |
An L4 program built for commercial reality, not demos.
Mining. Construction. Agriculture.
Geofenced L4 autonomy for off-highway machinery — haul trucks, dozers, harvesters, sprayers — operating 24/7 in dust, low-light, and extreme temperatures on private roads.
Haul-truck automation
Long-cycle haul-road automation with cm-grade GNSS-INS, redundant perception, integration with mine dispatch.
Earthmoving & paving
Coordinated machine fleets — dozers, graders, pavers — with high-accuracy positioning and task-level autonomy.
Field operations
Tractors, harvesters, sprayers with row-level precision, autonomous boundary follow, and crop-aware planning.
Port & terminal
Container yard tractors and shuttles in confined operational areas with human worker coexistence.
| Conditions | Dust, mud, low-light, extreme temperatures — sensors and compute selected accordingly Ruggedized |
| Accuracy | ±0.1 m lateral, cm-grade vertical for grade control where required RTK GNSS |
| Uptime | 24/7 with predictive maintenance, depot-charging or fueling integration Industrial-grade |
| Regulation | Private-road; ISO 17757 + AS/NZS 4801 + site-specific safety Off-road codes |
The shortest path to real, deployable L4 revenue.
Physical AI beyond the car.
The same autonomy primitives that drive cars also drive AMRs, yard tractors, sidewalk delivery bots, and humanoids. We adapt the Negits stack to the embodied-robotics domain.
AMR fleets
SLAM, multi-camera + radar perception, coordinated fleet behavior in human-rich environments.
Sidewalk & curb robots
Pedestrian-grade autonomy with VLA policies for nuanced human interaction at low speeds.
Tractors & shuttles
Heavy embodied autonomy in semi-structured yards with mixed human-vehicle traffic.
Mobility layer for humanoids
The locomotion + navigation + situational-awareness substrate for general-purpose humanoid platforms.
| Speed regime | Adapted for 3–8 m/s operation; tighter turning, finer trajectory granularity Re-tuned |
| Policy | VLA models with human-interaction reasoning baked in Foundation-model based |
| Safety | ISO 3691-4 (industrial trucks) or ANSI / RIA R15.08 (mobile robots) Domain-appropriate |
The convergence of autonomy & robotics is already here.
White-label IP for OEM RFQs.
Modular autonomy and cockpit IP that Tier-1s can configure and quote into OEM programs — with pre-configured BOM templates, safety case scaffolding, and SoC-port matrices for fast RFQ response.
Configurable stack
Full Negits stack licensed with white-label rights. Configurable by feature set, SoC, and sensor mix.
Quote-ready BOM templates
Pre-configured BOM templates by tier and region — for fast, credible RFQ response against tight OEM timelines.
Multi-SoC matrix
Pre-tested ports across NVIDIA, Qualcomm, TI, Mobileye, Renesas, Horizon — so you can match RFQ-specified silicon.
Auditable scaffolding
Safety case templates tailored per-OEM with proven acceptance history. Speeds homologation negotiations.
| Model | License + per-vehicle royalty · joint-development · OEM-specific carve-outs Flexible |
| RFQ response | 90-day RFQ-to-quote with pre-configured options Aggressive |
| Branding | White-label · Tier-1-branded delivery to OEM Quiet partner |
Win the RFQ. Ship to the OEM. Quietly.
Certified partner
solution provider.
Negits Solutions is a certified partner across key enterprise technologies, working closely with leading SaaS, cloud, and data platform companies — bringing accredited expertise to every engagement.
Where we lead.
Enterprise data
Experts in enterprise data integration, data engineering, and data analytics — from real-time streaming to warehouse-scale analytics.
Agile & SAFe
Certified solution provider for agile methodologies with key SAFe coaches, transformation leads, and Atlassian partnership.
Multi-platform delivery
Accredited delivery on cloud, data, integration, ERP, HCM, CRM, and analytics platforms — with the credentials to back every claim.
Hyperscale & data cloud.
Integration fabric partners.
Twelve practice areas, credential-backed.
Negits brings dedicated practices across the technology landscape — from application support through modern application development and platform integration.
& Maintenance
Business Analytics
& Testing
Experience & Mobility
Content & Social
Relationship Mgmt
Integration
Omni-Channel
Resource Planning
Management
Development
Integration
Silicon & vehicle platforms.
Beyond the basics.
Credentials matter. Delivery matters more.
Global delivery. Local presence.
Headquartered in Singapore with delivery centers across NAFTA, EMEA, India, and APAC — Negits delivers follow-the-sun coverage with regional engineering depth and customer-aligned program management.
Eight countries. One delivery org.
Singapore
- Worldwide headquarters
- Program management
- APAC customer handling (AUS, NZ, JPN, CHN, SE Asia)
- Salesforce development
- Strategic sourcing
- Global partnerships engagement
San Jose, CA
- Silicon Valley innovation hub
- AI & foundation-model research
- Customer engagement — tech & SaaS
- Automotive partnerships (NVIDIA, Qualcomm)
- Enterprise solution architecture
- US West Coast onsite services
Michigan, US
- NAFTA delivery center (US, Canada, Mexico)
- US onsite services
- NAFTA customer engagement
- Autonomous Drive Center of Excellence
- HRMS (Workday) solutions offerings
- Cloud application development
Dubai, UAE
- EMEA delivery center (Europe, Middle East, Africa)
- Program management
- Product development
- Finance Center of Excellence — solution offerings
London, UK
- Sub-location site for PROD support
- European customer engagement
- UK financial-services delivery
Chennai · Bangalore · Hyderabad
- Chennai — R&D location
- Bangalore — development hub
- Hyderabad — engineering and data delivery
- ODC handling for worldwide customers
- COE setup for enterprise technologies
- AAD — All About Data Practice (data engineering, integration, analytics & science)
- Offshore delivery center
Philippines & Vietnam
- Sub-location sites for staffing
- PROD support coverage
- Follow-the-sun support window
Follow-the-sun. Onshore + offshore.
Customer-aligned
San Jose, Michigan, London, Dubai, Singapore — for client engagement, solution architecture, and program leadership in customer time zones.
Delivery scale
Chennai, Bangalore, and Hyderabad — the engineering scale and centers of excellence for development, data, integration, and support.
Coverage extension
Philippines and Vietnam — staffing extension and round-the-clock PROD support coverage in the APAC time zone.
Wherever your program lives, we're nearby.
Let's build something
that ships.
Whether you're a CTO scoping a 10-year roadmap, a program lead with a perception gap, or an investor needing diligence — we'd like to hear what you're working on.