Omnigraph is an open-source object-storage native graph database with branching and typed ontology. It allows AI agents safely collaborate on shared knowledge. Give agents one typed graph with Git-like branching, review, and merge for every write, so changes can be validated before becoming shared context. Run it on your own S3-compatible storage, with semantic, keyword, and hybrid search plus graph traversal in one query. No hosted memory API or proprietary storage required.
Hi Product Hunt 👋 Omnigraph is an open source graph database where agents can safely collaborate and write to the same graph.
It has a typed ontology, branches and time travel, and hybrid search with graph traversal in the same query. Your graph lives in your own object storage in an open format.
More and more work inside a company is done by agents. They read the same data, write to it, make decisions on it, act on it. Without one shared world model they can trust, every agent ends up with its own version of the truth.
Omnigraph is a foundation for that shared world model. You can use it to build:
a company brain: people, projects, decisions, how they connect, all kept current by agents
context graphs for agents that work together on the same job
research graphs: papers, claims and the evidence behind them
I really like the design 😍 curious about a practical use case in B2B Sales. For example, connecting CRM HubSpot data with Linkedin Sales Navi insights, identify relevant decision-makers inside companies, then to map existing supplier and competitor relationships, and as to highlight potential places where I can meet these people in person(trade shows, conferences).
And as a final step, use profiles we've built to come up with relevant topics for the first touchpoint, conversation,presentation etc...
So, if we somehow figure out web scraping in our data protected world, Omnigraph could be pretty good place to store and connect all that data, right?
git style branching and merge for every agent write makes so much sense. congrats Andrew
Hey Product Hunt, I'm Andrew, co-founder and CTO of Modern Relay👋
I've worked with graphs for 18 years. I saw the power of graphs and ontologies early on, and I've been betting on them ever since.
Once agents became the main operators of graphs, it was clear to me that graph databases had to be rebuilt from first principles. That's what we set out to do with Omnigraph. We designed it as a database for agents first, and that choice shaped everything else.
Agents work at a very different pace from people. In one piece of work, an agent can create a branch, propose a schema change and bulk-load data. People don't work that way, and that's where conventional databases break.
Graphs are also getting much bigger, because agents process far more data than people do. Graph holds more than nodes and edges. It holds documents, video and other blobs that agents can embed and traverse from. Plus the full history of every change.
That's why Omnigraph runs on object storage.
The rest of the design follows from the same idea. A fully typed schema and declarative config make AI first-class operator of the database, and long-running agents can keep their state in it.
A graph used to be a small database on the side. Now it's becoming the main database and the foundation of the context layer. It holds the semantics agents need to reason over.
I'd love to hear about your experience. If you run agents on a graph today, where does it break first? And if you have questions about Omnigraph, ask them here. I'm around all day👀
branches make sense when multiple agents are proposing edits to the same shared graph
seeing which facts would be overwritten before merging would help catch conflicting updates
Congrats on the launch! How do agents usually write to the graph: do they get the schema up front, or does Omnigraph infer the entities and relationships from what they store? I'm also curious how it handles conflicting facts from different agent runs.
The visuals look super crisp, great job on that too! Also curious - how does it compare to the competitors?
Congrats on the launch, @pronskiy. I like that it’s basically Git for agents. Good luck today!
About Omnigraph on Product Hunt
“Open source graph database for your AI agents”
Omnigraph launched on Product Hunt on November 12th, 2026 and earned 141 upvotes and 12 comments, earning #3 Product of the Day. Omnigraph is an open-source object-storage native graph database with branching and typed ontology. It allows AI agents safely collaborate on shared knowledge. Give agents one typed graph with Git-like branching, review, and merge for every write, so changes can be validated before becoming shared context. Run it on your own S3-compatible storage, with semantic, keyword, and hybrid search plus graph traversal in one query. No hosted memory API or proprietary storage required.
Omnigraph was featured in Open Source (69.1k followers), Developer Tools (523k followers) and Database (2.3k followers) on Product Hunt. Together, these topics include over 113.2k products, making this a competitive space to launch in.
Who hunted Omnigraph?
Omnigraph was hunted by Ben Lang. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Omnigraph stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ben Lang
Hi Product Hunt 👋 Omnigraph is an open source graph database where agents can safely collaborate and write to the same graph.
It has a typed ontology, branches and time travel, and hybrid search with graph traversal in the same query. Your graph lives in your own object storage in an open format.
⭐ GitHub (MIT): github.com/ModernRelay/omnigraph
What can you use it for
More and more work inside a company is done by agents. They read the same data, write to it, make decisions on it, act on it. Without one shared world model they can trust, every agent ends up with its own version of the truth.
Omnigraph is a foundation for that shared world model. You can use it to build:
a company brain: people, projects, decisions, how they connect, all kept current by agents
context graphs for agents that work together on the same job
research graphs: papers, claims and the evidence behind them
You can check template ready-to-run graphs with real seed data (company brain, VC operating system, industry intel, beads): https://github.com/ModernRelay/omnigraph-cookbooks
What you get
Agents don't overwrite each other. Each one writes on its own branch, and you can review the changes before they reach main.
You always know who changed what and when, and you can see the graph as it was last week.
You define granular permissions to agents and humans in code.
Your schema says what can exist, and writes that don't fit are refused.
Agents find things by meaning or by keyword, then follow the connections over graph, in one query.
The graph lives in your own S3 bucket as open files you can take anywhere.
Every company needs a context layer, and we built Omnigraph to be the foundation for it.
Try it
The fastest way is to let your agent do it. Paste this into Claude Code, Codex or any coding agent:
Thanks @benln for hunting us! The whole team is here all day: @ragnor, @altshuler, @pronskiy, @azim_afroozeh. Ask us anything!