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Knowledge Base

A Knowledge Base lets your AI agent answer questions using your own documents. Upload FAQs, product docs, policies, or any text content, and the agent will search for relevant information when responding to customers.

What is a Knowledge Base?

A Knowledge Base is a collection of documents that your agent can reference. When a customer asks a question, the agent:
  1. Searches the knowledge base for relevant content
  2. Retrieves the most relevant chunks
  3. Includes that context in its prompt
  4. Generates an informed response
This approach is called RAG (Retrieval Augmented Generation).

Use Cases

Via Dashboard

1

Navigate to Knowledge Bases

Go to Senders > select your sender > Agent tab > Knowledge Bases section.
2

Create Knowledge Base

Click Create Knowledge Base and enter:
  • Name: A descriptive name (e.g., “Product FAQs”)
  • Description: What this knowledge base contains
3

Add Documents

Click Add Document and choose how to add content:
  • Text: Paste text content directly
  • Markdown: Upload .md files
  • PDF: Upload PDF documents
  • URL: Import content from a webpage
4

Wait for Processing

Documents are automatically chunked and embedded. This takes a few seconds for small documents, longer for large PDFs.
You’ll see a processing indicator while chunks are being created. The agent can only use fully processed documents.
5

Verify

Check the document list to see:
  • Chunk Count: Number of searchable chunks created
  • Processing Status: Whether the document is ready

Via API

Create Knowledge Base

Add Document

List Knowledge Bases

List Documents

Delete Document

How RAG Works

Processing Steps

  1. Chunking: Documents are split into smaller pieces (~500-1000 tokens each)
  2. Embedding: Each chunk is converted to a vector using an embedding model
  3. Indexing: Vectors are stored for fast similarity search
  4. Retrieval: When a question arrives, we find the most similar chunks
  5. Generation: Retrieved chunks are included in the LLM prompt as context

Supported File Types

PDF processing extracts text only. Images, charts, and tables within PDFs are not processed.

Document Limits

Best Practices

Structure Content

Use headers, bullet points, and clear sections. Well-structured content creates better chunks.

Be Specific

Include specific answers to common questions. The more explicit, the better the retrieval.

Keep Current

Update documents when information changes. Outdated content leads to incorrect answers.

Separate Topics

Create separate documents for different topics. This improves retrieval accuracy.

Content Writing Tips

Good document structure:
Poor document structure:
Write documents as if you’re answering specific customer questions. This makes retrieval more accurate.

Example Documents

FAQ Document

Product Document

Next Steps

Setup Guide

Configure your AI agent settings

Add Tools

Let your agent execute actions

Create Flows

Build structured conversation paths

AI Agents Concept

Learn how agents work under the hood