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ML / AI 2024-03

RAG Support Assistant

Internal RAG-powered support assistant with Slack integration, OpenAI, and ChromaDB. Reduced manual ticket resolution time by 20% at CVS Health.

20% Faster Resolution
RAGOpenAIChromaDBSlackPythonLLM

Overview

Built an internal Retrieval-Augmented Generation (RAG) support assistant at CVS Health that integrates with Slack to provide self-serve troubleshooting for engineering teams. The system uses OpenAI for generation and ChromaDB for vector storage, achieving a 20% reduction in manual ticket resolution time.

Key Features

  • Slack Integration: Native Slack bot for seamless team interaction
  • RAG Architecture: ChromaDB vector store for document retrieval, OpenAI for answer generation
  • Self-Serve Troubleshooting: Teams can resolve common issues without filing tickets
  • Context-Aware Responses: Retrieves relevant documentation and past solutions

Impact

  • 20% reduction in manual ticket resolution time
  • Accelerated onboarding for new team members
  • Reduced load on platform support teams
  • Improved knowledge discoverability across engineering organization

Tech Stack

  • AI/ML: OpenAI API, ChromaDB (vector database), RAG pipeline
  • Integration: Slack Bot API
  • Backend: Python, FastAPI
  • Data: Internal documentation corpus, runbook collection

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