AI Solutions for Automotive Companies
The automotive AI development company shipping production-grade systems across OEM, fleet, and aftermarket organisations, built ISO 26262 native inside your AWS VPC.
TRUSTED BY CONGLOMERATES, ENTERPRISES, AND STARTUPS ALIKE
Automotive AI Systems Built to Ship in Actual Production
Most automotive AI stalls at the pilot demonstration. Kodexo Labs delivers production-grade systems into your live OEM, fleet, and aftermarket environments, architected around ISO 26262 and ASPICE from day one, self-hosted entirely inside your AWS VPC.
Agentic AI and Multi-Agent Systems
Automotive workflow agents that handle diagnostic search, fleet routing, supplier coordination, and warranty triage on their own. LangGraph runs the multi-step work across OEM and fleet settings without a hand-off breaking, so a task opening in one system closes in the next, with no engineer left to stitch steps by hand.
Faster parts lookup · Diesel Laptops diagnostic search across 160,000 records
AI-powered products shipped · Across 25+ industries
Client retention rate · Multi-year automotive and fleet engagements
Eight AI Patterns Automotive Teams Run in Production Right Now
Automotive AI is no longer experimental. These patterns already run on real vehicles, fleets, and aftermarket platforms. Kodexo Labs has shipped systems against each one, fit to the operating environment of an OEM, a fleet operator, or an aftermarket business.
Automotive AI that has shipped to production, with the numbers to prove it
Diesel Laptops (Inc. 5000)
Fleet technicians were spending more time searching repair records than fixing trucks. Kodexo Labs built a self-hosted AI search system on AWS VPC that answers queries across 160,000 records in seconds.
85%
Search Time Reduction
160,000+
Repair Records Indexed
12 Weeks
Build to Production
Extensiv (Inc. 5000)
Extensiv's operations team waited on engineering for every data question. Kodexo Labs built an agentic LangGraph system that answers plain-English queries across 4 databases at 90%+ SQL accuracy.
90%+
SQL Accuracy
207
Tables
04
Databases
Teacher AI - Edtech Platform
Personalised tutoring had never scaled affordably. Kodexo Labs built Teacher AI to give every student a tutor in their native language, on demand. The in-house product now generates $5M+ in revenue.
50,000+
Users
30+
Countries
$5M+
Revenue
SmartMedHx (HIPAA-compliant)
Clinicians were losing nearly an hour daily to manual note-taking. Kodexo Labs built a HIPAA-compliant system that captures the patient interview and writes the clinical note automatically.
42
Providers
493
Patient Interviews
40%
Faster Interview Cycles
Sell The Trend
Sellers were typing keyword guesses and missing the products they wanted to source. Kodexo Labs rebuilt the visual-search engine so a single photo returns the right match instantly.
92%
CV accuracy (up from 65%)
88%
Speed Improvement
We hold each Kodexo Labs automotive build to these standards well before it ships into a vehicle.
We hold each Kodexo Labs automotive build to these standards well before it ships into a vehicle.
Sovereignty First
Every system we make runs inside your own AWS VPC. Telemetry, diagnostic records, and OEM source never cross a third party line, so security and compliance sign off with no exceptions.
Compliance Evidence
ISO 26262 cases, ASPICE Level 3 work products, and 21434 threat models ship alongside the code under the V-model. Your safety team gets an audit-ready package, not a late retrofit doc.
Protocol Native
AUTOSAR Classic and Adaptive on the ECU, J1939 for heavy duty telematics, and OBD-II for light duty fleets are built in as first class transport, not bolted on through brittle adapter.
Built for OEM engineering teams, fleet operators, and aftermarket platforms
The same delivery model serves three distinct automotive buyer profiles, each with different compliance obligations and different definitions of success.
OEM Engineering Teams.
AUTOSAR Classic and Adaptive integration delivered against ASIL B to D safety cases, with ASPICE Level 3 process evidence produced sprint by sprint. Kodexo Labs supports Tier 1 supplier qualification artefacts, V-model traceability matrices, and the homologation documentation OEM safety boards require before a feature reaches a production vehicle program.
Commercial Fleet Operators.
Predictive maintenance models trained on J1939 and OBD-II telematics streams, route optimisation that accounts for live load and driver-hours rules, and downtime reduction dashboards that connect to existing TMS platforms. The objective is fewer roadside events, longer mean-time-between-failures, and measurable fuel and asset utilisation gains.
Aftermarket Parts Platforms.
RAG-powered semantic search over parts catalogs, service bulletins, and diagnostic codes, with FAISS indexing tuned for technician query patterns. For Diesel Laptops, the architecture indexed 160,000 records inside an AWS VPC and produced an 85% improvement in lookup speed for the technician workforce.
Why Automotive Teams Choose Kodexo Labs Over Their Generalist AI Vendors
Generic AI shops learn automotive on your dime. We bring patterns shipped from real OEM programs, real fleet rollouts, and the true homologation work needed instead.
Capabilities Built to Fit the Full Automotive Tech Stack
What this build genuinely looks like beneath the marketing. The four clusters below describe the architectures, pipelines, and regulatory artifacts each produces, written for the CTO who needs assurance the automotive system holds together at component level.
[1]
Retrieval and Diagnostic AI
Parts catalogs, service bulletins, and diagnostic records retrieved semantically in under a second with no keyword noise. A FAISS-backed RAG layer attaches citations so technicians verify the source. LangGraph agents coordinate diagnostics, routing, supplier triage, and warranty workflows, and every agent step is logged for compliance review. Diesel Laptops is the reference implementation.
[2]
Compliance and Security
The pipeline produces ISO 26262 V-model artefacts, ASPICE Level 3 work products, and ISO/SAE 21434 threat models as code ships, ready for the customer safety board. Encryption is AES-256 at rest and TLS 1.3 in transit. Network controls, identity policy, and audit logging are designed against the 21434 threat model and reviewed by the customer security team.
[3]
Data and Vehicle Integration
Integration targets: AUTOSAR Classic and Adaptive on the ECU side, J1939 for heavy-duty telematics, and OBD-II for light-duty fleet ingestion, all treated as first-class transports. Telematics streams ingest directly into AWS VPC pipelines. Predictive maintenance models score failure probability from J1939 sensor streams, ranking component wear by remaining useful life rather than a static schedule.
[4]
Perception and Applied ML
Perception pipelines built with PyTorch and validated against ISO 21448 SOTIF scenarios, carrying ASIL B to D safety cases through to homologation evidence. GPT-4o-powered in-vehicle assistants stay grounded in technical service libraries and operator manuals, citing the source bulletin on every answer so drivers and technicians can trust the output in the field.
The Tech Stack Behind Clinical AI That Ships
These are the tools we actually use in production healthcare builds. Not a marketing capability list, just the stack our engineers reach for on day one of a new project.
How We Engineer Compliant Clinical AI Platforms
A predictable process is itself a compliance asset in regulated healthcare. Every step produces the documentation a future audit will require.
Discovery and Scoping
Clinical workflow mapping with the practitioners who use the system daily. Interviews span clinical, IT, and compliance, plus an audit of EHR integrations and data sources. The output is a written requirements specification covering every compliance obligation.
Architecture and Compliance Design
System architecture, data flow diagrams, encryption planning, and API contracts are developed collaboratively in parallel. We identify the compliance frameworks: HIPAA and HITECH always, FDA wherever a device is involved, SOC 2 wherever the buyer requires this.
Agile Build and Integration
Sprint-based delivery on a two-week cadence with weekly clinician demos. HL7/FHIR integration and EHR connector work runs in parallel with the model training. Decisions are documented in plain English, so compliance and clinical teams remain aligned throughout.
Compliance and QA Review
HIPAA audit trail validation, penetration tests, access control checks, and FDA software validation where applicable. Independent QA runs against the step one specification. No release ships until every compliance gate passes and the evidence is captured first.
Launch and Live Monitoring
Production deployment with SLA-backed uptime targets and real-time monitoring dashboards. Inference quality, latency, and error rates are tracked from minute zero. Retraining cadence is set in the contract, not left to chance. Support matches the build cadence.
Frequently Asked Questions
A healthcare AI development company builds the production software that runs clinical AI in real environments. That includes documentation AI, diagnostic decision support, ambient voice AI, EHR integrations, and medtech device software. Each build is engineered for HIPAA, HITECH, and HL7/FHIR from the first sprint.
Share Your Healthcare Project's Vision
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