Enterprise RAG Chatbot for Knowledge Management by Muhammad UsmanEnterprise RAG Chatbot for Knowledge Management by Muhammad Usman

Enterprise RAG Chatbot for Knowledge Management

Muhammad Usman

Muhammad Usman

๐—ž๐—ป๐—ผ๐˜„๐—น๐—ฒ๐—ฑ๐—ด๐—ฒ ๐—•๐—ฎ๐˜€๐—ฒ ๐—”๐—œ ๐—”๐˜€๐˜€๐—ถ๐˜€๐˜๐—ฎ๐—ป๐˜ -๐—ฆ๐—น๐—ฎ๐—ฐ๐—ธ ๐—•๐—ผ๐˜

Problem Solved: Company with 200+ employees wasting 15+ hours weekly searching through scattered documentation, Slack threads, and internal wikis for answers.
Solution Delivered: Built enterprise RAG chatbot using LangChain and n8n deployed directly in Slack Ingested data from Confluence, Google Drive, Notion, Slack history Created semantic search across all company knowledge Employees simply @ mention the bot in any Slack channel for instant answers Bot responds in threads to keep channels organized Implemented source citations with clickable links for every answer Bot learns from upvotes/downvotes to improve responses
Business Impact: Reduced time spent searching for information by 82% Answered 85% of internal queries instantly Improved onboarding time for new employees by 45% Saved approximately 60 hours weekly across the organization
Tech Stack: LangChain, OpenAI Embeddings, ChromaDB, n8n, Slack Bolt API, Notion API, Google Drive API, Confluence API
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Posted Oct 5, 2025

Developed a Slack bot to streamline company knowledge access, reducing search time and improving efficiency.