Research, Reports, and Guides
for Enterprise AI Leaders
Benchmark studies, technical whitepapers, implementation guides, and case studies — all grounded in real enterprise deployments.
Case Studies
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Building Marketing Intelligence Sovereignty
A governed AI Agent Factory for marketing intelligence, product knowledge, and social response workflows.
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.
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.
Latest from the Blog
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Agentic Memory, Priced: Why Fluree Memory Is the Token-Efficient Way to Give Agents Context
Transcript replay is the hidden tax on every agentic workflow. Here’s how write-back agentic memory keeps per-question context flat — and the AI bill predictable.
Why AI Needs a Knowledge Graph: Durable Data, Explicit Meaning, Consistent Answers
LLMs generate language — they don’t know your business. Why explicit meaning, durable data assets, and answers you can repeat make knowledge graphs the missing foundation for enterprise AI.
Fluree in Production: Why JSON-LD Native Beats JSON-LD Compatible for Enterprise AI
Not all RDF databases treat JSON-LD the same way. A production-criteria comparison of Fluree, Stardog, GraphDB, AllegroGraph, and RDFox — benchmark, comparison table, and a decision framework for 2026.
Whitepapers, Guides & Reports
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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
AI Playbook for Insurance Carriers
A practical playbook for insurance carriers building AI on top of policy, claims, and underwriting data — without ripping out existing systems.
AI Playbook for Regional Banks
How regional and community banks can deploy AI grounded in their own customer, transaction, and servicing data — with governance and provenance built in.
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