DEV.co
AI Frameworks · Ironclad

rivet

Rivet is an open-source visual IDE and TypeScript library for building complex AI agent workflows and prompt chains. It supports multiple LLM providers (OpenAI, Anthropic Claude, AssemblyAI) and vector databases, and can be embedded into applications via its npm packages.

Source: GitHub — github.com/Ironclad/rivet
4.6k
GitHub stars
384
Forks
TypeScript
Primary language
MIT
License (OSI-approved)

Key facts

Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.

FieldValue
RepositoryIronclad/rivet
OwnerIronclad
Primary languageTypeScript
LicenseMIT — OSI-approved
Stars4.6k
Forks384
Open issues105
Latest releaseapp-v1.11.3 (2025-08-08)
Last updated2026-06-13
Sourcehttps://github.com/Ironclad/rivet

What rivet is

Rivet provides a desktop application (Electron-based, available for macOS, Linux, Windows) and TypeScript libraries (@ironclad/rivet-core, @ironclad/rivet-node) for orchestrating LLM graphs. It abstracts multi-provider LLM calls, embeddings, and speech-to-text integrations through a node-based visual editor and programmatic API.

Quickstart

Get the rivet source

Clone the repository and explore it locally.

terminalbash
git clone https://github.com/Ironclad/rivet.gitcd rivet# follow the project's README for install & configuration

Need it deployed, integrated, or customized instead? DEV.co ships production installs.

Best use cases

Rapid AI Agent Prototyping

Teams can visually design complex prompt chains and agent workflows without extensive coding, iterate quickly, and then embed the resulting graphs into production applications via the TypeScript SDK.

Multi-Model LLM Orchestration

Applications requiring integration with multiple LLM providers (OpenAI, Anthropic Claude variants, AssemblyAI) benefit from Rivet's unified interface and centralized configuration management.

Embedding AI Workflows in Existing Applications

TypeScript/Node.js applications can import @ironclad/rivet-core or @ironclad/rivet-node to execute Rivet-designed graphs, enabling bidirectional communication between application code and AI orchestration logic.

Implementation considerations

  • Rivet graphs are executed via TypeScript SDK imports; ensure your Node.js/TypeScript build pipeline and runtime support dynamic graph loading and serialization.
  • LLM API credentials (OpenAI, Anthropic, AssemblyAI) must be securely injected at runtime; document credential management strategy before deployment.
  • The desktop application is available via GitHub releases; establish an update/deployment process for team use and decide whether to self-host binaries or rely on GitHub releases.
  • Graph serialization format and backward compatibility across versions are not explicitly documented; validate your CI/CD and version-pinning strategy for reproducibility.
  • 105 open issues suggest ongoing development; monitor the changelog and test new releases in staging environments before production adoption.

When to avoid it — and what to weigh

  • Non-TypeScript Application Stack — The SDK is TypeScript-centric (@ironclad/rivet-core, @ironclad/rivet-node). Other language ecosystems (Python, Go, Java) lack first-class integration; custom adapters would be required.
  • Strict Real-Time Latency Requirements — No performance or latency benchmarks are documented. Applications requiring sub-100ms response times should evaluate Rivet's overhead empirically before committing.
  • High Security/Compliance Isolation Needs — No security audits, penetration test results, or compliance certifications (SOC 2, FedRAMP, etc.) are documented. On-premises deployments and air-gapped environments may require custom hardening.
  • Private LLM-Only Deployments — Rivet's documented LLM support focuses on commercial providers (OpenAI, Anthropic, AssemblyAI). Support for self-hosted or on-premises LLM inference is not mentioned; custom implementation may be needed.

License & commercial use

Rivet is licensed under the MIT License, a permissive OSI-approved license permitting commercial use, modification, and distribution with minimal restrictions (include original license and copyright notice).

MIT License permits commercial use. However, using Rivet for commercial purposes should include the original MIT license text and copyright notice in your distribution. No commercial support, SLAs, or indemnification are documented; verify your organization's policy on using community-maintained open-source software in production.

DEV.co evaluation signals

Editorial assessment — not user reviews. Directional, with an explicit confidence level.

SignalAssessment
MaintenanceActive
DocumentationAdequate
License clarityClear
Deployment complexityModerate
DEV.co fitGood
Assessment confidenceHigh
Security considerations

No security audits, penetration test reports, or vulnerability disclosure policy are documented. LLM API keys and vector DB credentials must be managed securely; Rivet's credential storage mechanism in the desktop app and SDK is not detailed. Ensure credential injection does not leak keys into logs or serialized graph files. Evaluate supply chain risk: @ironclad/rivet-core and dependencies are maintained by Ironclad; monitor for dependency vulnerabilities.

Alternatives to consider

LangChain / LangGraph

Python/TypeScript libraries for orchestrating LLM chains with broader language support, larger community, and more extensive documentation. Better for non-TypeScript stacks.

Prompt Flow (Microsoft)

Visual DAG-based workflow designer integrated with Azure ML and multiple LLM providers. Stronger enterprise security/compliance posture and Microsoft support.

Flowise

Open-source low-code platform for building LLM applications with visual flow builder. No TypeScript SDK requirement; different UX and feature set.

Software development agency

Build on rivet with DEV.co software developers

Download Rivet, design your first agent graph, and integrate it into your TypeScript application. Join the Discord community for support and best practices.

Talk to DEV.co

Related open-source tools

Surfaced by semantic similarity across the DEV.co open-source index.

Related on DEV.co

Explore the category and the services that help you build with it.

rivet FAQ

Can I use Rivet in production?
Yes, via the TypeScript SDK. However, no SLAs, commercial support, or security audits are documented. Evaluate your organization's risk tolerance for production use of community-maintained open-source software.
What LLMs and vector databases does Rivet support?
LLMs: OpenAI (GPT-3.5, GPT-4), Anthropic Claude (Instant, 2, 3 variants), AssemblyAI LeMUR. Embeddings/Vector DBs: OpenAI Embeddings, Pinecone. Support for other providers or self-hosted LLMs is not documented.
How do I embed Rivet graphs in my application?
Use @ironclad/rivet-core (general) or @ironclad/rivet-node (Node.js specific). Import and call the graph execution API with serialized graph definitions and runtime context. See the integration getting started docs.
Is there a Python SDK?
Not documented. Rivet is TypeScript-focused; Python applications would need custom HTTP/RPC adapters or wrappers around the Node.js SDK.

Work with a software development agency

From first prototype to production, DEV.co delivers software development services around tools like rivet. Our software development agency staffs experienced software developers and web developers for custom software development, web development, integrations, and ongoing support across ai frameworks and beyond.

Ready to Build AI Workflows?

Download Rivet, design your first agent graph, and integrate it into your TypeScript application. Join the Discord community for support and best practices.