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Automate M&A due diligence, enterprise risk assessment, business intelligence, and other tasks on top of clean, coherent, governed, enterprise-wide data
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Run LLMs on top of Fluree AI and/or use it as its own LLM layer
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MCP native, use with Claude, Cursor and others; supports more than 300 connectors
Fluree, the AI data platform company and a Gartner Cool Vendor in AI Data Management, announced the general availability of Fluree AI, a serverless knowledge graph platform that makes data AI-safe. With Fluree AI, agents pull from an intelligent data layer that encompasses the entire organization—with permission and governance. Automation becomes trustworthy because it draws from an organized, clean institutional memory rather than data siloes.
“You can only automate complex business functions when agents pull on trustworthy data,” said Fluree Co-CEO Brian Platz. “Even the most powerful LLM fails when the underlying data is incomplete, contradictory, and unsecured. How much of your organization you can automate is ultimately limited by the quality and coherence of your data.”
Enterprises currently use a proliferation of AI agents, each an expert in its limited domain and with a unique governance- and security framework. Agents can’t share context, don’t know if the same records exist in other departments, and produce contradictory answers.
“Our ability to use our enterprise data to drive strategic decisions has become a business imperative,” said Eric Chacon, CIO, Hometap. “Tools like Fluree, which enable us to use frontier models to conduct formal, trustworthy analytics, are a priority for this year.”
Fluree AI provides a shared schema, persistent context between sessions, learning across workflows, and enterprise-controlled permissions. Organizations and LLMs can finally reason over relationships and history. Cross-functional workflows such as M&A due diligence, enterprise risk assessment, and regulatory compliance become possible.
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How it works
Fluree AI runs on a fully serverless architecture that scales horizontally with demand. Enterprises requiring full isolation can deploy Fluree AI entirely within their own AWS account as a versioned, self-contained stack.
In addition to providing an intelligent data layer for LLMs, Fluree AI can be used as its own agentic layer. For example, ask Fluree AI to build a dashboard and generate live updates as new data lands. Or design an agent that will monitor metrics, KPIs, and external signals on a schedule, then deliver a ranked morning briefing with recommended actions that a user can approve with one click.
Fluree AI is native to the Model Context Protocol, so Claude, Cursor, and any MCP clients can query it as a first-class tool with no custom integration. Fluree AI also supports more than 300 connectors — including Salesforce, HubSpot, Snowflake, Postgres, BigQuery, Databricks, Stripe, and Google Sheets — with automatic schema inference and entity resolution. Security and access control are enforced inside the data itself, at the most granular level, so permissions follow the data into every conversation and every agent. Every dataset is historically queryable, and every answer carries a signed record of how it was derived. Because LLMs query the knowledge graph rather than a data silo, Fluree AI also requires fewer tokens to retrieve information than a traditional LLM setup.
Proven Foundation
Fluree’s semantic graph technology already powers mission-critical AI and analytics workloads for organizations including the U.S. Department of Defense, Morgan Stanley, the Associated Press, Dow Jones, Warner Bros. Discovery, and Arizona State University.
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