Your archive is an asset. Treat it like one.
Decades of stories, footage, and licensed content sit in systems that can’t answer a question. Fluree turns the archive into governed, AI-ready knowledge — searchable in plain English, with rights and provenance attached.
Trusted by publishing & media leaders
The most valuable content you own is the hardest to use.
Publishers sit on generational libraries of premium content — but the metadata that would make them searchable, licensable, and AI-ready never kept up.
Decades of untagged archive content
Broadcast footage, photo libraries, and back-catalog stories were never catalogued to modern standards. Content nobody can find can’t be reused, repackaged, or sold — no matter how valuable it is.
Rights metadata scattered everywhere
Licensing terms, clearance status, and usage windows live in contracts, spreadsheets, and tribal knowledge. Every reuse decision turns into a legal research project instead of a lookup.
Editorial research buried in silos
Reporters and producers re-research stories the newsroom has already covered, because institutional knowledge is split across CMSs, archives, wikis, and inboxes that don’t talk to each other.
Four ways media teams put Fluree to work.
One product behind every workflow below: Fluree AI, for tagging unstructured content and governing your taxonomies.
Content knowledge graph
Connect stories, people, places, and events across every property into one semantic layer your teams — and your AI — can query with full context.
Explore knowledge graphsArchive search & cataloguing
Fluree auto-tags video, audio, text, and images against your controlled vocabularies, bringing decades of uncatalogued backlog online through one governed pipeline.
Explore archival & cataloguingContent monetization & licensing
Package rights-cleared inventory against advertiser briefs in minutes — with fit scores and brand-safety status attached to every asset.
Explore content monetizationRights-aware AI assistants
Ground assistants in your knowledge graph with GraphRAG, so every answer respects licensing terms, cites its sources, and stays inside your editorial standards.
Explore GraphRAGExplore the Fluree AI capabilities behind it: content tagging and taxonomy management.
Customer case study — Global beauty brand
Building Marketing Intelligence Sovereignty
A global beauty brand built a governed AI Agent Factory on Fluree — turning fragmented marketing, product, and social knowledge into faster, more reliable, MCP-connected decision support.
5
agent factory functions
Zero
hallucination target
MCP
AI model connectivity
Multi-source
marketing knowledge unified
Go deeper on the media stack.
Two dedicated solution pages walk through the workflows in detail — from bringing the backlog online to packaging it for revenue.
Archival & Cataloguing
Make decades of backlog searchable. Auto-tag every format against your own vocabularies and give editorial teams one place to look.
Visit the solution pageContent Monetization
Turn the searchable archive into sellable inventory — packaged against advertiser briefs with brand-safety status attached.
Visit the solution pageField notes on taxonomies, graphs, and AI.
Practitioner writing from the Fluree team on the ideas behind archive intelligence — how vocabularies, ontologies, and knowledge graphs make content AI-ready.
Controlling LLMs with Enterprise Taxonomies
How governed vocabularies turn taxonomies into the grounding layer for enterprise AI.
Taxonomies Versus Ontologies: A Short Guide
A practitioner’s guide to the models that power content discovery — and when to use each.
How to Create a Knowledge Graph for Analytics
A step-by-step walkthrough of building a knowledge graph that analytics teams actually use.
Publishing and media data questions, answered.
Short answers to what content, rights, and data leaders at publishers ask us most.
How can publishers make an archive searchable and AI-ready?
By tagging it against your controlled vocabularies and governing it in one knowledge graph. Fluree auto-tags video, audio, text, and images, bringing decades of uncatalogued backlog online through one governed pipeline.
What is a knowledge graph for publishers?
It is a semantic layer that connects stories, people, places, and events across every property. Your teams and your AI can query it with full context, instead of searching separate CMSs, archives, and wikis.
How do media companies track licensing and rights for archive content?
By making content rights-aware. Licensing terms, clearance status, and usage windows become part of the data, so a reuse decision is a lookup instead of a legal research project.
Can AI assistants use our content without breaking licensing or editorial standards?
Yes, when they are grounded in your knowledge graph with GraphRAG. Every answer then respects licensing terms, cites its sources, and stays inside your editorial standards.
How can a publisher package archive content for advertisers?
Package rights-cleared inventory against advertiser briefs in minutes, with fit scores and brand-safety status attached to every asset.
How do newsrooms stop re-researching stories they already covered?
By connecting institutional knowledge that is split across CMSs, archives, wikis, and inboxes into one semantic layer. Reporters and producers can then find what the newsroom already knows, with full context.
Do we need to replace our existing systems?
No. Fluree turns your archive into governed, AI-ready assets without replacing the systems you already run.
Put fifty years of content to work.
Book a demo and see how Fluree turns your archive into governed, AI-ready assets — without replacing the systems you already run.
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