Research, Reports, and Guides for Enterprise AI Leaders

Turning Unstructured Data Into Knowledge Your AI Can Trust

Roughly 80% of enterprise knowledge sits in PDFs, contracts, transcripts, and meeting notes your AI can’t query. This session turns those documents into a governed knowledge graph: ontology-grounded extraction with evidence for every fact, entity resolution across CRM exports and notes, and a deterministic parser that keeps costs predictable at scale. Recorded October 1, 2026.

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Case Studies

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Case StudyBeauty & cosmetics

Building Marketing Intelligence Sovereignty

A governed AI Agent Factory for marketing intelligence, product knowledge, and social response workflows.

5 core functionsMCP-readyCited answers

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Case StudyFinancial services

Streamlining Distribution and Access to Trends through a Data Portal

An AI-driven data portal architecture that automates semantic tagging, topic discovery, and search relevance.

500K documents10x knowledge baseReal-time discovery

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Case StudyGovernment & environmental science

Making 30 Years of Biodiversity Data AI-Ready — in a Single Platform

A biodiversity knowledge platform that unifies structured records and field content into one governed GraphRAG-ready graph.

6M+ records60+ appsGraphRAG-ready

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Latest from the Blog

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BlogOct 23

Context Graph vs Knowledge Graph: What’s the Difference?

A context graph is a knowledge graph that also records decisions, provenance, time and policy, so agents know what was decided, why, and under which rules.

Kevin DoubledayRead

BlogOct 23

How to Build a Context Layer for AI: Step-by-Step Guide

Build a context layer for AI in nine steps: start with one decision-grade use case, model the ontology, resolve entities, add policy, serve agents via MCP.

Kevin DoubledayRead

BlogOct 23

How to Build a Knowledge Graph: Step-by-Step Guide

To build a knowledge graph, plan one use case, model an ontology, integrate and resolve data, extract from documents, then validate, query and maintain.

Kevin DoubledayRead

Videos & Tutorials

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Webinar Replay

Turning Unstructured Data Into Knowledge Your AI Can Trust

Brian Platz & Andrew Johnson

0:56

Product Demo

FlureeDB Overview

Fluree for Unstructured Data: Extract Knowledge

0:56

Product Demo

Fluree for Unstructured Data: Extract Knowledge

Whitepapers, Guides & Reports

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Guide· Knowledge Graphs

Fluree Reference Architecture (2026)

The current technical overview: what’s inside the context layer, what data moves and what stays put, interfaces, policy and audit, deployment, dated benchmarks and the license.

5 min read

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Guide· Data Governance

From Taxonomy to Governed Ontology

A field guide for teams that already have an enterprise taxonomy and now need it to carry governance and AI: six moves from taxonomy to governed ontology, where the data migration fits, four worked examples, and a 12-question readiness checklist.

12 pages · 10 min read

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Whitepaper· Enterprise AI

The Tokenomics of Enterprise AI

Why enterprise AI bills tripled while token prices collapsed 99.7% — and the five-year TCO math for putting a governed knowledge graph with agentic memory between your agents and your data.

15 pages · 12 min read

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Our blog covers the same topics — GraphRAG, knowledge graphs, semantic layers, enterprise AI — without the gate. Read for free, then come back when you want the deep dive.

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