Build a Document QA Engine — Your Team Answers Any Question From Slack

How to build a RAG-powered system that lets any team member ask any question about your company documents — and get an accurate, source-attributed answer in seconds, directly in Slack.

The average employee spends 1.8 hours per day searching for information. Policies, procedures, product specifications, legal agreements, historical decisions — all of it exists somewhere in your company's documents, but finding the right answer requires knowing which document to look in, where to look, and whether the information is current.

What You Are Building

A Slack slash command that queries a RAG pipeline built on your company documents. Any team member types /ask followed by their question. The system searches your indexed documents, retrieves the most relevant sections, and returns a precise answer with the source document name and section. The whole interaction takes under 5 seconds.

Phase 1: Build the RAG Pipeline in Flowise

Create a Flowise cloud account. Upload your documents — policies, product specs, legal agreements, meeting notes, up to 500 pages. Configure chunking: 1000 character chunks with 200 character overlap. Use OpenAI text-embedding-3-small for cost efficiency (significantly cheaper than ada-002 with comparable quality). Connect Pinecone or Supabase as the vector store for production use.

Set your system prompt: "You are a knowledgeable assistant with access to the company documents provided. Answer questions using ONLY information in those documents. Always cite the source document and section. If the answer is not in the documents, say: 'This information is not available in the provided documentation.' Never use outside information."

Phase 2: Connect to Slack via Make.com

Create a Slack app with slash command support. Set the slash command URL to a Make.com webhook. In Make.com: receive the webhook → extract the question text → call the Flowise API endpoint with the question → format the response with source attribution → post back to Slack using the response URL from the original slash command payload.

Quality Monitoring

Log every query to a Google Sheet: question, answer, source cited, timestamp. Review weekly. Questions that get "This information is not available" answers reveal gaps in your documentation. Questions that get wrong answers reveal chunking or retrieval issues. Both are fixable — and the log tells you exactly where to focus.