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Tools/Rivet vs Graphiti
Rivet

Rivet

framework
vs
Graphiti

Graphiti

framework

Rivet vs Graphiti — Comparison

Overview
What each tool does and who it's for

Rivet

An open-source AI programming environment using a visual, node-based graph editor

Rivet is a visual programming environment for building AI agents with LLMs. Iterate on your prompt graphs in Rivet, then run them directly in your application. With Rivet, teams can effectively design, debug, and collaborate on complex LLM prompt graphs, and deploy them in their own environment. At Ironclad, we struggled to build AI agents programmatically. Rivet's visual environment, easy debugger, and remote executor unlocked our team's ability to collaborate on increasingly complex and powerful LLM prompt graphs. Visualize and build complex chains to create applications for production — not just prototyping. See what's under the hood and observe the execution of prompt chains in your application, in real-time. Rivet graphs are just YAML files, so you can version them in your team's repository, and review them using your favorite code review tools. Rivet's visual programming environment is a game-changer. The visual nature of the tool, paired with how collaborative it is, allows us to create complex chains for AI agents in drastically less time than it would take in other environments. It's the best tool out there. Rivet really addressed some limitations that we were hitting up against... and some we didn't know we had. The visualization makes a big difference when working through agentic logic and really makes it easy to see what the AI is doing. But the ability to debug and collaborate across the team made a huge difference as well - we've used it to launch our virtual mortgage servicing agent and are excited to see how the tool continues to evolve. In order to build great product experiences we have to be able to iterate quickly. Leveraging tools like Rivet allows us to more accurately understand the tradeoffs between things like speed and quality as we build AI-powered experiences in Bento. Rivet is an amazing tool for rapidly prototyping and visually understanding complex AI workflows. It's been wonderful collaborating with Ironclad to integrate AssemblyAI's audio transcription and understanding models into the Rivet ecosystem. We're excited to see what developers create equipped with such a powerful and capable toolkit! Domenic Donato, VP of Technology Rivet is a super slick and compelling tool for prompt construction and LLM composition, particularly when you're trying to combine AI with many existing tools and APIs. I can see this becoming a popular tool for those working on robust and reliable AI applications. Ironclad Contract AI (CAI) is a virtual contract assistant, powered by AI agents, and developed with Rivet. CAI is capable of answering diverse questions about every stage of the contract lifecycle, directly using Ironclad's existing capabilities, like contract search, workflow process, and data visualization. Start building AI agents with Rivet in just a few simple steps! Welcome to the Rivet User Guide! Rivet is a powerful Integrated Development Envir

Graphiti

Build Real-Time Knowledge Graphs for AI Agents. Contribute to getzep/graphiti development by creating an account on GitHub.

Based on the provided content, there are no reviews or social mentions specifically about "Graphiti." All the social media mentions are about GitHub Copilot, Figma, npm registry tools, and other development-related topics, but none reference a tool called "Graphiti." Without actual user feedback about Graphiti, I cannot provide a meaningful summary of user sentiment, strengths, complaints, or pricing opinions for this specific tool.

Key Metrics
—
Avg Rating
—
0
Mentions (30d)
33
4,528
GitHub Stars
24,254
367
GitHub Forks
2,403
—
npm Downloads/wk
—
—
PyPI Downloads/mo
—
Community Sentiment
How developers feel about each tool based on mentions and reviews

Rivet

0% positive100% neutral0% negative

Graphiti

0% positive100% neutral0% negative
Pricing

Rivet

tiered

Graphiti

per-seat + tiered
Use Cases
When to use each tool

Graphiti (1)

Quick Start
Features

Only in Rivet (3)

Visualize and BuildDebug RemotelyCollaborate

Only in Graphiti (10)

Build context graphs that evolve with every interaction — tracking what's true now and what was true before.Give agents rich, structured context instead of flat document chunks or raw chat history.Query across time, meaning, and relationships with hybrid retrieval (semantic + keyword + graph traversal).Python 3.10 or higherNeo4j 5.26 / FalkorDB 1.1.2 / Kuzu 0.11.2 / Amazon Neptune Database Cluster or Neptune Analytics Graph + Amazon OpenSearch Serverless collection (serves as the full text search backend)OpenAI API key (Graphiti defaults to OpenAI for LLM inference and embedding)Google Gemini, Anthropic, or Groq API key (for alternative LLM providers)Connecting to a Neo4j, Amazon Neptune, FalkorDB, or Kuzu databaseInitializing Graphiti indices and constraintsAdding episodes to the graph (both text and structured JSON)
Developer Ecosystem
8
GitHub Repos
11
157
GitHub Followers
417
20
npm Packages
13
15
HuggingFace Models
—
—
SO Reputation
—
Product Screenshots

Rivet

Rivet screenshot 1

Graphiti

Graphiti screenshot 1Graphiti screenshot 2Graphiti screenshot 3
Company Intel
information technology & services
Industry
information technology & services
790
Employees
6,000
$331.2M
Funding
$7.9B
Series E
Stage
Other
Supported Languages & Categories

Rivet

AI/MLAnalyticsDeveloper Tools

Graphiti

AI/MLFinTechDevOpsSecurityAnalytics
View Rivet Profile View Graphiti Profile