Automotive AI
Cybertron Labs
Automated the V-model for the first safety-aware engineering AI serving German Tier-1 OEMs.
The challenge
Automotive requirements engineering is one of the most labor-intensive processes in the industry. Engineers manually write, review, cross-reference, and validate thousands of requirements against safety standards like ISO 26262 and ASPICE. Cybertron's core program had stalled under that complexity.
What we built
Document parsing and ingestion automation
Pipelines that parse, extract, and structure data from DOORS exports, PDFs, and specification sheets. No manual data entry, no copy-paste.
Semantic search engine
Engineers query thousands of requirements in natural language. Finding related requirements, conflicts, and gaps drops from days to seconds.
Requirements generation and elicitation
Automated generation of new requirements from existing specifications, gap detection, and refinement suggestions grounded in safety standards and domain knowledge.
V-model engineering automation
End-to-end lifecycle automation from specification through design, implementation, testing, and verification. Traceability that used to live across spreadsheets now runs as a pipeline.
Development environment automation
Infrastructure as Code on AWS, CI/CD pipelines, containerized services, automated testing, and deployment workflows. New engineers are productive on day one.
ROI
Results
Outcome
A 72-hour intervention became a 16-month strategic partnership. Enigma now architects and builds Cybertron's next-generation AI technology stack. Deep neural networks and automated engineering pipelines became Cybertron's core competitive advantage.
Technologies
"Enigma has been a true partner, solving our toughest challenges and accelerating our progress. When we needed custom AI, they delivered flawless results in days. We trust Enigma for high-stakes innovation.
Ahmed AbdienCEO and Founder, Cybertron Labs
