Agent in a Box

Document Q&A Agent

operations
1

The Problem

Your company has hundreds of documents—policies, procedures, product specs—but nobody can find anything. People ask the same questions repeatedly, and tribal knowledge lives in senior employees' heads.

The Solution

An AI agent that ingests your documents and answers questions in natural language, always citing its sources so answers can be verified.

How It Works

  1. Ingest: Documents uploaded to vector database
  2. Index: Content chunked and embedded for semantic search
  3. Query: User asks question in Slack or web interface
  4. Retrieve: Agent finds relevant document chunks
  5. Answer: Generates response with source citations

Tool Stack

  • Pinecone/Weaviate: Vector database
  • OpenAI Embeddings: Document vectorization
  • Claude/GPT-4: Answer generation
  • n8n: Workflow orchestration
  • Slack: User interface (or custom web app)

Example Prompt

You are a helpful assistant that answers questions based on company documentation. 

Rules:
- Only answer based on the provided context
- Always cite which document(s) you used
- If the answer isn't in the context, say "I couldn't find this in our documentation"
- Be concise but complete

Context from documents:
{{retrieved_chunks}}

User question: {{question}}

Provide your answer with citations in this format:
[Answer]

Sources:
- [Document name, page/section]

Implementation Tips

  • Start with a focused document set (e.g., just HR policies)
  • Chunk documents thoughtfully—too small loses context, too big reduces accuracy
  • Include document titles and sections in chunks for better citations
  • Set up feedback mechanism: "Was this helpful? Yes/No"

When to Use This

  • Same questions asked repeatedly to HR/IT/managers
  • Onboarding takes too long because info is scattered
  • Employees can't find policies when they need them
  • Knowledge silos are becoming a problem

Limitations

  • Quality depends on document quality—messy docs = messy answers
  • Won't understand complex multi-step questions well
  • Needs document refresh process as content changes
  • Doesn't replace human judgment for nuanced situations