OpenBook vs Relevance AI
Relevance AI is a polished, closed-source SaaS for building agent 'workforces.' OpenBook delivers a comparable agentic builder — visual canvas, agents, tools, multi-agent flows, human approvals — but open source and self-hostable, so your data, prompts, and model keys stay on your infrastructure with no per-credit billing.
At a glance
OpenBook and Relevance AI, capability by capability.
| Capability | OpenBook | Relevance AI |
|---|---|---|
| Open source | ||
| Self-hostable | ||
| Visual agent builder | ||
| AI builds the workflow | Partial | |
| Multi-agent flows | ||
| Human-in-the-loop | ||
| Bring your own model keys | Limited | |
| No per-credit billing |
Why teams pick OpenBook over Relevance AI
Open source & self-hosted
Run it on your own box, read every line, and bring your own keys. Relevance AI is a closed SaaS.
No credit metering
No per-run credit pricing — you pay your model provider directly. Predictable at any volume.
Own your data and prompts
Nothing leaves your infrastructure unless you send it. Critical for regulated or privacy-sensitive teams.
Extensible by design
An open plugin model and a generic HTTP connector instead of a fixed catalog.
MIT, self-host, your keys.
Closed SaaS with credit-based pricing.
When to choose which
- You need to self-host for privacy, compliance, or cost control
- You want to avoid per-credit metering and vendor lock-in
- You want to read and extend the source
- You want a fully managed SaaS and don't need to self-host
- You prefer a curated, supported commercial catalog over open extensibility
Recreate each Relevance agent as an OpenBook agent (prompt + actions), and each multi-step flow as a workflow graph. The AI builder can scaffold the graph from a description.
Frequently asked questions
Build your first agentic workflow today.
OpenBook is free and open source. Self-host it in minutes, or read the docs to see how far the engine goes.