AI Knowledge Base Agent
The AI Knowledge Base Agent enables you to create an autonomous AI agent trained specifically on your company’s proprietary data. By uploading documents, scraping website URLs, and automatically indexing historical WhatsApp chats, the AI learns your organization’s context to handle customer inquiries intelligently.Overview
The Knowledge Base Agent combines multiple data sources into a unified vector database (powered by Qdrant), allowing your AI to provide accurate, context-aware responses based on your organization’s knowledge.All vectorized data is strictly partitioned using tenant/organization IDs to ensure complete data isolation between different Eazybe clients.
Key Features
Multi-Source Knowledge Base
Train your agent using three powerful data sources:Web Links
Input any URL to scrape website content, help center articles, documentation, or blog posts. The agent automatically extracts and indexes the text content.
File Upload
Drag and drop documents directly into the platform. Supported formats include:
- PDF files
- DOCX documents
- TXT files
- CSV spreadsheets
Agent Configuration
Customize your agent’s behavior with these settings:- Agent Name: A unique identifier for your agent (e.g., “Acme Support Bot”)
- Role/Persona: Define how the AI should behave (e.g., “You are a helpful customer support representative for Acme Corp”)
- Base Prompt: Set the foundational instructions that guide all agent responses
- Fallback Action: Configure what happens when the AI is uncertain (e.g., “Handover to human agent”)
Real-Time Indexing Progress
Vectorizing large documents or thousands of chats takes time. The interface provides clear visibility into the indexing process:One-Click WABA Deployment
Once your agent is fully trained and indexed, deploy it to any connected WhatsApp Business API (WABA) number:How It Works
1. Creation Phase
Click Create New Agent and provide a name and description for your AI agent.2. Data Ingestion Phase
Upload your knowledge base materials:- Drag and drop product PDFs, policy documents, or training materials
- Paste URLs from your website, help center, or documentation
- Enable Sync WhatsApp History to include historical conversations
3. Processing Phase
The backend processes your data through these steps:- Chunking: Large documents are broken into manageable segments
- Embedding Generation: Each chunk is converted to a vector embedding
- Storage: Embeddings are stored in Qdrant with proper tenant isolation
- Indexing: A searchable index is built for fast retrieval
4. Ready State
Once indexing reaches 100%, the agent’s status changes to Ready to Deploy. You can review the indexed sources and make adjustments if needed.5. Deployment Phase
Select your WABA number and deploy. The AI now intercepts incoming messages on that number and responds based solely on your ingested knowledge base.6. Live Operation
The deployed agent handles customer inquiries 24/7, using only the information from your knowledge base to generate accurate, contextually relevant responses.Important Considerations
Data Isolation & Security
Long-Running Uploads
For large knowledge bases (e.g., 5,000+ WhatsApp chats):- Indexing happens asynchronously via a background worker
- The UI polls for status updates every few seconds
- You can navigate away from the page during indexing
- Return anytime to check progress via the agent dashboard
Stale Knowledge
If your knowledge sources change (website updates, new product docs, policy changes):- Navigate to your agent’s Data Sources section
- Click Re-sync next to the affected source
- The system updates the embeddings in Qdrant with the latest content
Fallback Routing
When the AI encounters a query it cannot confidently answer based on the knowledge base, it follows your configured fallback action:Best Practices
Start Small
Begin with a focused knowledge base for a specific use case (e.g., product FAQs, return policy). Expand gradually as you monitor performance.Quality Over Quantity
- Use well-structured, up-to-date documents
- Clean PDFs with clear formatting produce better results
- Avoid duplicate or conflicting information
Monitor and Iterate
- Review conversation logs to identify knowledge gaps
- Add missing documents to improve coverage
- Refine the base prompt based on real interactions
Test Before Deploying
Always test your agent thoroughly with sample queries before connecting it to your live WABA number.Troubleshooting
Agent Not Responding
- Verify the WABA number is properly connected
- Check that the agent status is Live (not just Ready)
- Ensure the knowledge base indexing completed successfully
Inaccurate Responses
- Review the knowledge base for conflicting information
- Check that relevant documents were properly indexed
- Refine the base prompt to be more specific
Indexing Stuck
- Large file uploads may take considerable time
- Check file sizes—files over 50MB may need to be split
- If stuck for more than 30 minutes, contact support
Missing WhatsApp Chats
- Verify the Sync WhatsApp History toggle is enabled
- Check that chat permissions are granted
- Ensure chats are within the sync date range