Fluree
Data + Context for AI and Apps
339 followers
Data + Context for AI and Apps
339 followers
Fluree is an enterprise AI data platform and verifiable knowledge graph database that combines immutability, security, and semantic graph capabilities. It operates as a unified intelligence layer, helping organizations connect fragmented information into a single "source of truth" to power zero-hallucination AI agents, analytics, and decentralized data sharing
This is the 3rd launch from Fluree. View more
Fluree AI
Launching today
Fluree AI gives every app and AI agent the same trusted context from your company data. Ask questions and get cited, verifiable answers from one live data layer, with permissions checked on every request. Instead of rebuilding prompts or relying on RAG guesses, Fluree queries structured data directly and connects to MCP-ready agents, dashboards, and apps in minutes.
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Launch Team / Built With
Fluree
Hey Product Hunt — Brian here, CEO of Fluree.
The backstory:we spent years building governed, verifiable graph data infrastructure for enterprises — provenance, permissions, cryptographic audit trails, the unglamorous stuff.
Then LLMs arrived, and suddenly the entire world had our problem: AI that's brilliant at language and terrible with data. Hallucinated numbers. Context that resets every conversation. Five tools, five silos, five versions of the truth.
Fluree AI is our answer: an intelligence layer that sits under everything you build.
Here's the flow:
Throw everything at it. CSVs, databases, docs, SaaS exports. Fluree classifies your data and connects the dots automatically — the graph builds itself.
Plug in any AI. Claude, OpenAI, Gemini, Ollama — any MCP-speaking agent reasons over the same graph. No tools yet? Ours is built in.
Get answers you can prove.Responses are structured queries against the graph, not generated guesses — so every answer is cited, permissioned, and reproducible. If the data is correct, the output is correct.
Build unlimited interfaces on one foundation. This is the part that changes how you work: ask a question, then say "make that a dashboard," then "turn it into an app my team can use," then "deploy an agent that watches this." Chats, dashboards, apps, and agents all read from — and write back to — the same governed graph. You stop rebuilding context in every tool. It compounds instead.
Most software starts from the UI and traps your data underneath it. We think the future starts with the right data + context — and then any interface you want becomes cheap to build and safe to trust.
Getting started takes ~2 minutes: sign up free, drop in a dataset (messy is fine — that's the point), and ask your first question. No demo call, no sales gate.
I'll be in the comments all day with our engineering team. Ask us anything — and if you think "cited, verifiable answers" sounds too good, please come try to break it. Genuinely. That's the fun part.
What I find genuinely useful here is the permissions-per-request model. I've seen access control get bolted on as an afterthought in other AI setups, and it always shows. Building it into the query layer itself feels like the right instinct, not a patch.
Fluree
@ramish_saje Thanks Ramish!
That was a deliberate call. If we handle security and permissions at the data layer, we never risk leakage at all. Handing that responsibility over to an LLM is certainly asking for disaster.
More on Fluree's query policies for those who want to go deeper :) https://labs.flur.ee/docs/db/security/policy-in-queries
I'm curious how Fluree handles data that changes rapidly, like real-time sensor feeds or transaction streams. Immutability sounds great for auditability, but I wonder if it creates friction when you need fast updates. Would love to see a breakdown of how they balance permanence with agility in practice.
How much effort does integration usually require for existing business applications? Ready connectors could shorten implementation time for customers.
Fluree
@alheri_murya Integration is quite easy - we have existing data models loaded up for common business apps, which means all you have to do is point a SaaS or Google Drive or Iceberg table (etc.) at Fluree and we map it to an ontology (an intelligent shared schema of concepts). So the integration work is up front but done-for-you.
This is the first data platform I've seen that treats security and semantics as equally important. Usually one gets sacrificed for the other. I'd like to know more about the tradeoffs.
how's pricing structured?
Fluree
@colton_hayes2 great question! We have a generous free tier and pricing is pay-as-you-go. Here's the cool thing: because Fluree AI runs serverless, there is zero idle cost to you. That truly means pay-as-you-go!
Our pricing unit is called "fuel." Fuel is combined compute + storage + LLM calls.
This feels like a direct answer to the RAG guessing problem I keep running into. My question is how fast the live data layer updates when source systems change. Real accuracy matters more than most teams admit.