Use case AutomotiveADAS
ADAS & autonomous validation
BOOK A DEMO 80% of regression checks run without a rig
1,000s of scenarios replayable without a physical re-test
95% faster scenario retrieval
Validation is a traceability problem
- ADAS validation teams run thousands of test scenarios across simulation, proving ground, and public road
- Each scenario generates multi-modal data: camera, radar, lidar, CAN, GPS, IMU
- ISO 26262 and SOTIF require traceability from test evidence back to the requirement being validated
Today, tests are recorded without context
- Data volumes are enormous and arrive from heterogeneous sources with no common schema
- Linking a sensor recording to the software version, map version, and scenario definition active at the time is done manually or not at all
- Replaying historical scenarios into updated models means re-running physical tests, because the data isn't queryable in context
Quix provides full configuration
- Quix ingests all sensor streams in parallel, normalises them, and links every recording to the scenario metadata and software stack at capture time
- Historical runs are stored as first-class queryable data; replaying a past scenario into a new model version is a software operation, not a re-test
- Traceability from sensor reading to requirement to test run is structural — built into the data model, not a document written after the fact
Build a searchable test history
- Test coverage evidence for safety cases is generated continuously, not assembled at programme milestones
- Regression testing cost drops: most regression checks happen on stored data, not on physical re-runs
- Engineers spend time on edge cases and failure modes, not on data archaeology