Correctness changes with context
The right behavior depends on vehicle and configuration, lifecycle and operating state, evidence and diagnostic confidence, safety boundaries and escalation. Generic scoring misses those interactions.
Solutions · Automotive
Automotive AI connected to engineering and service intent
Carry technical, quality, service, and safety judgment into the systems teams are building.
Automotive AI spans product engineering, manufacturing, service, and the driver experience. Teammately creates explicit behavioral standards for each context and their boundaries.
The domain reality
Generic quality is not enough for consequential automotive behavior.
The standard lives across specialist teams
Systems engineering, Quality and diagnostics, Dealer and service operations, Driver experience and safety each hold part of the judgment the system needs to behave well.
Real work is full of exceptions
A benchmark must represent edge cases, uncertainty, conflicting goals, and escalation—not only the most common automotive path.
Priority workflows
Start where expert judgment materially changes the answer.
Engineering copilots
Evaluate technical reasoning, requirements use, evidence, and uncertainty.
Diagnostic assistants
Test symptom interpretation, next steps, confidence, and safe escalation.
Service agents
Benchmark explanations and recommendations across vehicle and customer contexts.
In-vehicle assistants
Validate usefulness, distraction boundaries, scope, and safe fallback behavior.
Correctness blueprint
Connect specialist judgment to the benchmark and the build.
Your experts define
- Systems engineering
- Quality and diagnostics
- Dealer and service operations
- Driver experience and safety
The benchmark covers
- Vehicle and configuration
- Lifecycle and operating state
- Evidence and diagnostic confidence
- Safety boundaries and escalation
Your AI team receives
- A deliberate coverage map
- Explicit policies and binary rubrics
- Targeted cases, variants, and exceptions
- Inspectable evaluation and improvement evidence
One connected workflow
Five product capabilities, applied to one domain standard.
Coverage Engineering
Design the combinations of vehicle and configuration, lifecycle and operating state, evidence and diagnostic confidence, safety boundaries and escalation the benchmark must represent.
Correctness Elicitation
Turn judgment from systems engineering, quality and diagnostics, dealer and service operations, driver experience and safety into policies, applicability conditions, and binary rubrics.
Weave
Create targeted automotive cases, variants, artifacts, and worlds from the coverage plan.
Trialground
Run candidate models and agents in controlled environments and preserve the behavior-level evidence.
Coevolve
Explore parallel improvement directions and return newly discovered gaps to the right specialists.
What good looks like
A development team that can improve behavior without losing domain intent.
Coverage you can defend
Know which automotive conditions, exceptions, and risks the benchmark represents—and which it does not.
Judgment that scales
Reuse every specialist decision across policies, rubrics, evaluation, and future cases.
Evidence for every iteration
Compare model, prompt, harness, and agent changes against the same domain-grounded standard.
A controlled learning loop
Route unresolved questions and newly discovered gaps back to accountable experts.
Teammately evaluates behavior and development evidence; vehicle control and safety decisions remain with validated systems and authorized professionals.
Build a benchmark around how your automotive experts actually judge quality.
Start with a consequential workflow and the specialists already accountable for it. Teammately turns their judgment into reusable development infrastructure.