Automotive Regulatory Evidence Verification Copilot

Supports automotive teams with simulation consistency analysis, virtual certification testing, scenario-based ADS safety validation, and AI-assisted regulatory reporting across emissions, safety, and EV incentive documentation.

The Problem

“Automotive Compliance Verification Copilot for simulation validation, virtual certification, ADS safety assurance, and regulatory reporting”

Organizations face these key challenges:

Different simulators can produce conflicting ADAS safety conclusions for the same scenario

Physical headlamp testing is costly, weather-dependent, and difficult to schedule

ADS regulatory evaluation is ambiguous without structured scenario-to-requirement mapping

Compliance evidence is fragmented across PLM, ALM, simulation tools, data lakes, and document repositories

Manual emissions and EV incentive paperwork is error-prone and hard to scale

Regulatory reporting requires traceability, citations, and defensible approval records

Engineering and compliance teams use different vocabularies and data formats

Standards and regulations change frequently across regions and vehicle programs

Impact When Solved

Reduce manual compliance reporting effort by 40-70% through automated extraction, drafting, and validationShorten simulator comparison and discrepancy triage from days to hours with automated consistency analysisLower physical night-testing dependency by shifting more headlamp validation into virtual certification workflowsImprove ADS safety case completeness with scenario-based evidence mapping to UN GTR requirementsIncrease auditability through citation-backed outputs, versioned evidence, and approval workflowsCreate reusable compliance assets across emissions, safety, lighting, and EV incentive programs

The Shift

Before AI~85% Manual

Human Does

•Review every case manually
•Handle requests one by one
•Make decisions on each item
•Document and track progress

Automation

•Basic routing only

With AI~75% Automated

Human Does

•Review edge cases
•Final approvals
•Strategic oversight

AI Handles

•Automate routine processing
•Classify and route instantly
•Analyze at scale
•Operate 24/7

Real-World Use Cases

AI-assisted regulatory reporting, emissions extraction, and EV incentive documentation

AI gathers the right compliance data from many documents and prepares region-specific paperwork for regulators and EV incentive programs.

Compliance data extraction and document generation/validationscaling

10.0

Scenario-based safety validation for Automated Driving Systems (ADS) under UN GTR

Before a self-driving feature can be trusted, regulators define many driving situations and test whether the system behaves safely in them.

Scenario-based decision evaluation and safety assuranceemerging but formalizing through international regulatory work

10.0

Cross-simulator consistency analysis for ADAS test scenarios

Engineers run the same virtual driving test in two different simulators to check whether both tools agree, so they do not trust a safety result that only works in one software package.

Comparative validation and sensitivity analysisemerging methodology; clearly needed because simulator variability is highlighted as a current source of discrepancy.

10.0

Virtual intelligent headlamp testing and certification

Instead of waiting for the right night weather and test track conditions, engineers test smart headlights in a virtual night-driving lab.

Physics-based optical system validation with human-in-the-loop evaluationcommercial virtual testing application

10.0