Enterprise AI Copilot & Knowledge Graph for 8,500 Global Engineers
Zero-hallucination internal RAG system reducing developer onboarding time by 65%.
Initial Operational State
Novatech’s 8,500 distributed software and hardware engineers spent an average of 9.2 hours per week searching through 15 years of fragmented Confluence wikis, Jira tickets, CAD schematics, and GitHub repositories.
Engineering Intervention
Engineered a private, air-gapped enterprise generative AI copilot using custom fine-tuned open-source models (Llama-3 70B) connected to a hybrid vector and graph database. The system answers engineering questions with verifiable line-item citations.
Technologies & Infrastructure Stack
Step-by-Step Implementation Roadmap
Ingested and parsed 4.2 million technical documents with automated OCR and AST parsing.
Constructed a Neo4j knowledge graph linked with a high-speed Pinecone vector index.
Implemented strict role-based access control (RBAC) ensuring employees only query documents matching their security clearance.
Deployed an embedded desktop and IDE plugin allowing engineers to query internal code without leaving their editor.
Production Metrics & Results
Avora Services Leveraged in this Engagement
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