Vector Databases & Knowledge bases
Learn how to use vector databases and Knowledge bases in ajan to work with large document collections.
Vector Databases
Vector databases are databases that enable embedding searches. They allow you to store many/long documents and retrieve them later using an LLM.
ajan currently supports the following providers:
Setting Up a Connection
When working with vector databases, you first need to set up a connection in the respective integration's settings. Once the vector database is connected, it can be used in agents as an action or in chat with @. With each request, the model writes a request to the database and an embedding search is performed.
Knowledge bases
A Knowledge base is a collection of documents that can be used as knowledge. Knowledge bases use vector search within the product, so smaller use cases do not require setting up a separate vector database, and less technical users can work with many documents.
- Capacity — ajan Cloud supports up to 1,000 files. Dedicated deployments use their configured Knowledge base file limit.
Management
Open Library > Folders and select your Knowledge base to manage it. You can:
- Upload files
- Delete files
- Manage permissions
API Access
Alternatively, users can programmatically list Knowledge bases, manage access, rename them, or upload, update, or delete files via the Knowledge Folder API. A link can be included to reference the original source in responses to users.
Comparison: Knowledge bases vs. Custom Vector Database
Knowledge bases are suitable for less technical users and smaller use cases that need to be implemented quickly. For very large, valuable use cases with several thousand documents, a custom vector database is recommended because settings can be adjusted to the use case, paragraph length, topics, and metadata.
| Feature | Knowledge bases (ajan) | Custom Vector Database |
|---|---|---|
| Management | Fully managed by ajan, no infrastructure needed | Full control over models, dimensions, retrieval parameters, updates, etc. |
| Default Settings | Optimized defaults (up to 2,000-character chunks, 1536 dimensions, top-50 retrieval) | No predefined settings |
| Data Volume | Ideal for up to 1,000 files in ajan Cloud; dedicated deployments use their configured limit | Unlimited data volumes and custom data structures possible |
| Setup | Quick setup via ajan UI | Own infrastructure, maintenance, and connection via ajan Actions required |
| Access Control | Granular access control and UI management in ajan | Access control must be implemented yourself |
FAQ
Use a vector database when your organization already manages retrieval infrastructure or needs custom indexing, metadata, or search behavior. Use a ajan Knowledge base when you want ajan to handle document processing and retrieval.
Yes. Use them for different retrieval needs, but keep the setup focused. Too many overlapping sources can make answers less predictable and harder to debug.