AI & Data Infrastructure•Wholesale Distribution Company•2025
Intelligent Data Platform with Multi-RAG Architecture
Enterprise data hub connecting 14 sources with intelligent query routing using CAG, RAG, and GraphRAG technologies managed by AI agents based on query complexity.
14Data Sources Unified
2.4MRecords Synced Daily
85%Reporting Time Reduced
$340KRevenue Recovered
Python · LangChain · Neo4j · PostgreSQL · Pinecone · Claude · Apache Kafka · FastAPI · Redis · dbt
Deep Dive
The project was delivered in four stages over six months, building the data foundation first, then implementing progressively sophisticated retrieval methods.
| Stage | Focus Area | Status | Key Deliverables |
|---|---|---|---|
| 1 | Data Infrastructure | Completed | PostgreSQL warehouse, Kafka streaming, CDC pipelines for ERP/CRM/billing, data normalization, identity resolution across systems |
| 2 | CAG Implementation | Completed | Redis caching layer, frequently-accessed data preloading, context window optimization, sub-100ms response for common queries |
| 3 | RAG & GraphRAG | Completed | Pinecone vector store, Neo4j knowledge graph, entity extraction, relationship mapping, semantic search across documents |
| 4 | Agent Orchestration | Completed | Query complexity classifier, intelligent routing system, response synthesis, natural language interface, feedback learning loop |
