Data sharing agencies can trust. Governance they can prove.
Fluree gives government organizations a governed knowledge layer where policy travels with the data — so records can move across agency boundaries, feed AI safely, and prove their lineage on demand.
Trusted by
The mission spans agencies.
The data doesn’t.
Government data is fragmented by design — separate agencies, separate systems, separate rules. The result is that the hardest part of any mission isn’t collecting data. It’s sharing it without losing control of it.
Sharing data means surrendering it
Every inter-agency agreement becomes a bespoke integration. Copies proliferate across networks, ownership blurs, and the agency that originated a record loses the ability to govern how it’s used downstream.
Policy is bolted on, app by app
Access rules live in application code — rebuilt, re-audited, and re-broken for every new system. The same record ends up protected differently depending on which door a user walks through.
Decades of records AI can’t safely touch
Registries, filings, and field observations span generations of formats and systems. Without provenance and access control at the data layer, none of it can be handed to AI with confidence.
One governed data layer. Four ways agencies put it to work.
Fluree combines a semantic knowledge graph with policy enforcement and verifiable lineage inside the database itself — a foundation these four patterns share.
In production on three decades of government data.
Not a pilot, not a proof of concept — a national biodiversity knowledge base running on Fluree, governed end to end and ready for AI.
Customer case study
Making 30 Years of Biodiversity Data AI-Ready — in a Single Platform
A government department consolidated the biodiversity knowledge behind more than 60 applications — 6M+ species records spanning 30 years — into one governed platform, with sensitive-species access controls and GraphRAG-ready natural-language access.
6M+
species records unified
60+
downstream applications served
30 years
of historical knowledge modernized
Written by the people who build it.
Perspectives from Fluree’s founders and team on data-layer security, verifiable credentials, agentic AI, and public-sector compliance.
Why GenAI Security Starts at the Data Layer
AI agents on uncontrolled data inherit every SaaS vulnerability. Data-centric security that embeds policies at the data layer is the only durable fix.
Kevin Doubleday · Jan 2026
Context-in-the-Loop: The Architecture for Autonomous AI
AI agents fail not because they lack intelligence but because they lack context. Context-in-the-Loop is the next architectural step after HITL and RAG.
Brian Platz · Jun 2026
What Are Verifiable Credentials? Why Do They Matter?
Physical credentials are insecure the moment they touch digital systems. Verifiable credentials and DIDs give cryptographic trust without centralized risk.
Kevin Doubleday · Jan 2022
Leveraging Knowledge Graph Databases for EU Data Compliance
GDPR and the EU Data Governance Act demand transparency and access control. Knowledge graphs deliver consent management and data traceability by design.
Jan Verrept · Oct 2023
Government data questions, answered.
Short answers to what agency data, security, and modernization leaders ask us most.
How can government agencies share data across agencies without losing control of it?
By enforcing access policy at the data layer instead of in every consuming application. With Fluree, rules travel with the record wherever it goes, so the agency that originated a record keeps the ability to govern how it is used downstream.
What is a knowledge graph, and why do agencies use one?
A knowledge graph is a connected map of the entities and relationships a mission runs on, such as people, places, registries, and cases. Agencies use one to unify registries, case systems, and reference data into one durable, queryable layer, instead of building a bespoke integration for every agreement.
How does Fluree create an audit trail for government records?
Every change is tracked with verifiable lineage inside the database. FlureeDB’s cryptographic verifiability makes the audit trail part of the database, not a bolt-on.
Can government staff use AI on sensitive data safely?
Yes, when access policy is applied before the model sees the data. Fluree gives staff plain-language answers drawn only from data they are cleared to see, and every response is cited back to source records.
Why do AI agents need data-level security in the public sector?
Because AI agents on uncontrolled data inherit every SaaS vulnerability. Data-centric security that embeds policies at the data layer is the durable fix, so a record is protected the same way whichever door a user or agent comes through.
Can Fluree modernize decades of legacy government data?
Yes. A national biodiversity knowledge base runs on Fluree: 30 years of historical knowledge modernized, 6M+ species records unified, and 60+ downstream applications served. Natural-language access is enabled through GraphRAG.
How do we get started with Fluree in a government agency?
Start with the initiative that hurts most: cross-agency data sharing, records modernization, or AI governance. Talk it through with a Fluree specialist, who will show how policy enforced at the data layer changes what is possible.
Bring verifiable, governed data to your mission.
Talk through your agency’s data-sharing, modernization, or AI-governance initiative with a Fluree specialist — and see how policy enforced at the data layer changes what’s possible.
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