AI Knowledge Base Builder
A RAG-powered internal chatbot that answers team questions using your Confluence, Google Drive, and Slack history.
60%
Faster Onboarding
45%
Less Slack Noise
30hrs
Weekly Time Saved
92%
Answer Accuracy
Confluence
Document Source
Pinecone
Vector Database
Claude API
AI Synthesis
Retool
Chat Interface
The Problem
The Challenge
A 50-person engineering org had knowledge scattered across 400+ Confluence pages, thousands of Slack threads, 200+ Google Docs, and tribal knowledge locked in senior engineers' heads. New hires took 3+ weeks to become productive because they couldn't find answers. The same questions got asked repeatedly in Slack, creating noise and interrupting deep work. The Head of Engineering estimated the team was losing 30+ hours per week to knowledge-seeking overhead.
How We Fixed It
Our Solution
Crawled and indexed all Confluence spaces, Google Drive folders (Docs, Sheets, Slides), and 6 months of Slack Q&A threads using custom Python scripts.
Chunked documents intelligently — preserving context boundaries, headers, and code blocks — and generated embeddings using OpenAI's embedding model.
Stored all embeddings in Pinecone with rich metadata: source, author, last modified date, team, and document type for filtered search.
Built a Retool-based chatbot interface that accepts natural language questions, performs vector similarity search across all indexed content, and sends relevant chunks to Claude for answer synthesis.
Claude generates answers with source citations (clickable links to the original Confluence page, Slack thread, or Google Doc) so users can verify and go deeper.
Implemented an auto-learning loop: when someone asks a question in Slack that gets a helpful response, it's automatically indexed for future RAG retrieval.
Tools & Infrastructure
Tech Stack
Confluence
Primary knowledge source. 400+ pages of engineering docs, runbooks, architecture decisions, and process documentation indexed and searchable.
Pinecone
Vector database. Stores document embeddings with metadata for fast, semantically-aware similarity search across all knowledge sources.
Claude API
Answer synthesis engine. Takes retrieved context chunks and generates accurate, well-structured answers with source citations.
Retool
Internal chatbot UI. Provides a clean, searchable interface for the team to ask questions and browse answers with source links.
Impact & Outcomes
The Results
60%
Faster Onboarding
New hire onboarding time dropped from 3+ weeks to ~1 week as they could self-serve answers to any question instantly.
45%
Less Slack Noise
Repetitive questions in Slack dropped 45%, freeing senior engineers from constant interruptions.
30hrs
Weekly Time Saved
Team recovered 30+ hours per week previously spent searching for information across fragmented tools.
92%
Answer Accuracy
RAG chatbot answers are 92% accurate with source citations — users trust it as their first stop for questions.
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