Build Smarter ADAS with Product Validation Solutions

Identifies, curates, and analyzes rare, high-risk scenarios through real-world data, simulation, and expert insights. These edge cases expose systems to challenging conditions beyond typical test environments.

DDD specializes in curating edge cases, developing corresponding test cases, and analyzing system behavior to enhance resilience and safety in production deployments

Requirements-driven performance analysis approach evaluates autonomous system performance by verifying pre-defined technical and operational requirements using test data to assess system readiness for deployment.

DDD ensures each iteration meets its technical goals by conducting rigorous analysis, bridging the gap between system performance and defined requirements.

Requirements to results traceability establishes a transparent link between system requirements, test cases, and results, ensuring traceability from development to validation

DDD develops end-to-end traceability frameworks, ensuring that every test result directly contributes to validating system requirements and strengthening safety cases and regulatory approval processes.

A structured safety case compiles verification and validation artifacts to demonstrate system safety for regulatory compliance ensuring autonomous systems meet safety and performance standards before deployment.

DDD curates and expands safety datasets, aligning them with product requirements to reinforce safety claims and enhance confidence in system reliability.

Test coverage analysis Measures how thoroughly an autonomous system is tested across different operational parameters which helps quantify gaps, assess real-world representativeness, and identify edge case coverage.

DDD provides data-driven insights to improve test coverage, ensuring robust validation strategies that enhance system performance and reduce failure risks.