About
Rivet is an open-source visual AI programming environment developed by Ironclad, designed to help engineering teams build, iterate on, and deploy complex LLM-powered AI agents. Rather than coding prompt chains programmatically—which can be opaque and hard to debug—Rivet provides a node-based graph editor where each step in an AI workflow is a visual node connected by edges, making logic immediately visible and understandable. The tool supports remote debugging, allowing developers to observe the real-time execution of their prompt graphs as they run inside their actual applications. This closes the gap between prototyping and production by letting teams see exactly what the AI is doing at each stage. Collaboration is built into Rivet's architecture: graphs are stored as plain YAML files, meaning they can be version-controlled in any Git repository and reviewed with standard code review tools. This makes it easy for cross-functional teams—including engineers, product managers, and AI researchers—to contribute and review AI workflows together. Rivet integrates directly into Node.js and TypeScript applications, with a straightforward SDK for embedding prompt graphs in production services. It also supports integration with third-party AI capabilities, such as audio transcription and understanding models. Rivet is ideal for developers building production AI agents, virtual assistants, RAG systems, and complex multi-step LLM pipelines who need visibility, collaboration, and reliability beyond what coding alone can offer.
Key Features
- Visual Node-Based Graph Editor: Build complex AI agent workflows using an intuitive drag-and-drop node graph interface, making LLM logic visible and easy to reason about.
- Remote Real-Time Debugger: Observe prompt chain execution inside your live application in real time, bridging the gap between prototyping and production debugging.
- Team Collaboration via YAML: Graphs are stored as YAML files, enabling version control in Git repositories and standard pull request-based code reviews for AI workflows.
- Node.js & TypeScript Integration: Embed Rivet graphs directly into your Node or TypeScript application with a dedicated SDK for seamless production deployment.
- Extensible Ecosystem: Integrate third-party AI models and APIs—such as audio transcription, search, and data visualization—as nodes within your agent graphs.
Use Cases
- Building production-grade AI agents with multi-step LLM reasoning chains for enterprise applications.
- Visually prototyping and iterating on complex prompt workflows before deploying to production.
- Debugging AI agent behavior in real-time within live applications using the remote execution debugger.
- Enabling cross-functional teams to collaborate on and review AI logic using Git-based YAML workflows.
- Integrating external AI capabilities (e.g., transcription, search, data APIs) as nodes in agent pipelines.
Pros
- Free and Open Source: Rivet is fully open-source with no licensing costs, making it accessible to individuals and teams of any size.
- Production-Ready Debugging: Remote execution observability allows teams to debug AI agents in real production environments, not just sandboxed prototypes.
- Collaboration-First Design: YAML-based graph files integrate seamlessly with Git workflows, making it easy for teams to review, version, and iterate on AI logic together.
- Visual Clarity for Complex Workflows: The node-based interface makes even highly complex multi-step LLM chains comprehensible at a glance, reducing cognitive overhead.
Cons
- Requires Node.js/TypeScript for Full Integration: Production deployment is currently limited to Node.js and TypeScript environments, excluding teams using other backend languages.
- Desktop-First Experience: Rivet is primarily a downloadable desktop application, which may add friction compared to fully browser-based tools.
- Learning Curve for Visual Paradigm: Developers accustomed to code-first LLM frameworks may need time to adapt to the node-based visual workflow paradigm.
Frequently Asked Questions
What is Rivet?
Rivet is an open-source visual programming environment for building AI agents and complex LLM prompt graphs. It uses a node-based graph editor to let teams design, debug, and deploy AI workflows visually.
Is Rivet free to use?
Yes, Rivet is completely free and open-source. It is built and maintained by Ironclad and available on GitHub at no cost.
How does Rivet integrate with my application?
Rivet provides an SDK for Node.js and TypeScript applications. You design your prompt graphs in the Rivet desktop editor and then execute them directly within your application using the integration library.
How does team collaboration work in Rivet?
Rivet saves all graphs as plain YAML files, which can be committed to any Git repository. Teams can version-control, branch, and review AI graphs the same way they manage regular code.
Can I debug my AI agents in production with Rivet?
Yes. Rivet includes a remote debugger that lets you observe the real-time execution of your prompt graphs as they run inside your live application, giving you full visibility into each step of the AI workflow.
