Portfolio / DOMAIN AI & TOOL USE
AutoIntel AI
Turning diagnostic data into a clearer next step.
An automotive diagnostic architecture connecting domain knowledge, LLM reasoning, and tools.
The problem
Diagnostic codes need vehicle context and supporting evidence to become useful. Reasoning must acknowledge uncertainty and know when to escalate.
The solution
A domain-specific architecture combines RAG, tool calling, automotive APIs, and a collection of 30,000+ Diagnostic Trouble Codes for structured diagnostic reasoning.
Human controls
Evidence and escalation are explicit parts of the architecture. The system supports diagnostic decisions; qualified technicians retain responsibility for inspection and repair.
The outcome
An architecture for evidence-led diagnostic assistance that connects AI reasoning to automotive knowledge and tools. Measured performance and release status await verification.
SYSTEM FLOW
How the pieces work together.
The core capabilities and review points, in order.
- 01Vehicle context
- 02Diagnostic codes
- 03Knowledge retrieval
- 04Tools + reasoning
- 05Evidence
- 06Technician review
Building blocks
EXPLORE THE PRODUCT
Discuss the architecture.
No public demo is currently listed for this project.
Product visuals on this page are identity illustrations, not product screenshots.
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