The Problem
Automotive recalls are increasing in scale and cost — and software is the rising cause.
- 27.7M vehicles recalled in the US in 2024.
- Over 50% of recalls now stem from software & requirements failures.
- OEMs and Tier‑1 suppliers face billions in direct costs and long-term brand damage.
Quick reality check
Average global annual recall cost exceeds
2024 US recalls estimated at $15+ billion in direct and indirect costs.
Phoenix AI - The Solution
Embed compliance & safety insights into the R&D workflow so problems are caught in engineering, not at recall time.
Connected Evidence
Link software, requirements, regulations, recalls and accident data directly into engineers' tools and backlogs.
Active Compliance Guardrails
Flag mandatory test cases and highlight missing coverage before features ship.
Faster Reporting & Reviews
Reduce documentation, review and reporting time by 40–50% with AI-suggested fixes and test-cases.
How it Works
Phoenix AI combines the power of Retrieval-Augmented Generation and Context-Augmented Generatation
Ingest data
Engineering, compliance, and hardware information undergo careful dataset preparation and labeling before being harmonized into a searchable knowledge graph — creating a unified foundation for analysis and automation.
Analyse & connect
Phoenix AI maps traceability, identifies compliance gaps, and computes risk scores tied to modules and firmware.
Engineer support
An AI agent suggests fixes, generates test cases, drafts reports, and creates evidence packages ready for auditors.
Context-Augmented Test Case Generation
Phoenix AI also generates tests that understand the system:
- Reads and splits requirements into testable conditions.
- Pulls signal ranges, timing, and failure modes from your data.
- Generates unit tests, integration tests, and HiL-style scenarios linked back to requirements.
- Proposes edge and negative tests based on limits, regulations, and known failures.
Result: Test suites that trace back to requirements and cover realistic, safety-relevant scenarios.
Context-Augmented Code Generation
With Phoenix AI, code generation is no longer “generic boilerplate”
- Uses your coding rules (naming, patterns, safety checks).
- Adapts to your SDK / libraries instead of random ones.
- Aligns with linked requirements, so each function has a clear purpose.
- Adds boundary checks and safety logic based on retrieved constraints (e.g., torque limits, speed ranges).
Result: Code that actually compiles in your environment and fits into your existing architecture.
Software Security
Phoenix AI identifies potential cybersecurity vulnerabilities in code and architecture, suggesting mitigations aligned with automotive security standards like ISO/SAE 21434. The security agent can run static analysis as well as dynamic and fuzzing on virtual targets.
Agentic Continuous Integration Cycle
The Phoenix AI Agent can autonomously monitor code changes, runs compliance checks, and updates test cases in real-time, ensuring ongoing adherence to safety and regulatory standards throughout the development lifecycle.
Why it Matters
Phoenix AI combines the power of Retrieval-Augmented Generation and Context-Augmented Generatation
Without context augmentation, an LLM can only guess. With Phoenix AI, every answer is grounded in:
Your requirements → Your architecture → Your SDK → Your tests
That’s how Phoenix AI turns “Generic AI” into a real engineering copilot for code and test generation, and delivers code that is no longer “generic boilerplate”.
Get in Touch
Learn how Phoenix AI turns compliance into a competitive advantage.
Meet the Team
Habip Demirezen
Founder & CEO
- 15+ years of expertise in automotive software, AI, and system & development & validation, delivering mission-critical solutions at BMW, Daimler, SAIC, NIO, Geely, BAIC and BJEV.
- Track record of real-world impact, with ADAS features like Hands-Free Driving now in production vehicles.
- Led high-performance engineering teams across China (10 years) and Europe, executing multi-million-dollar projects and scaling innovation across global programs.
- Academic foundation in MSc. Distributed Computing and Dipl.-Ing. Embedded Systems, enabling deep-tech innovation in complex, safety-critical environments.
Timh Bergstrom
Founder & CTO
- Global Infrastructure Architect (20+ yrs) – Led large-scale cloud & edge platforms (AWS, GCP, on-prem) ensuring zero-downtime reliability for automotive AI and simulation systems.
- Automation & Reliability Expert – Advocate of “automate everything”; built safety-grade DevOps, IaC, and CI/CD pipelines powering deterministic vehicle validation workflows.
- AI/ML & Security Platform Lead – Deep expertise in LLM ops, vector DBs, Kubernetes, and Terraform — architecting Phoenix AI’s robust, compliant infrastructure layer.
- Innovation-Driven CTO – Serial founder combining cloud, AI, and Web3 R&D to deliver scalable, secure, and cost-efficient platforms for the automotive industry.