Make your archive searchable again.
Decades of video, audio, and text — minimally catalogued, buried in legacy systems, invisible to the teams who need it. Fluree’s AI catalogues your entire archive against your controlled vocabulary at scale: 100,000+ assets tagged in 24 hours. Every asset findable, every tag governed, every rights status attached.
What Is Archival & Cataloguing
AI that tags like your best archivist — at the speed of your entire library.
Your archive holds decades of premium content — news footage, documentaries, interviews, raw b-roll, audio recordings, photographs. Most of it was catalogued with outdated vocabulary, minimal metadata, or not catalogued at all. You own it. You can’t find it.
Generic cloud AI (Rekognition, Cloud Video AI) labels content fast — but the tags are inconsistent and don’t match your editorial taxonomy. "Person" instead of the journalist’s name. "Outdoor scene" instead of your location taxonomy.
Fluree CAM tags video, audio, text, and images against YOUR controlled vocabulary, governed in ITM — so every asset in every format becomes findable, connected, and ready for the AI era.
Connect any source.
CSV, API, Postgres, Snowflake, Salesforce — Fluree ingests it as-is. No schema migration. No pipelines to maintain.
Search 300+ sources…AVAILABLE SOURCESSalesforceApp · OAuthSnowflakeData lakePostgresDatabase · replicacustomers.csvCSV · 1.24M rows1.24M rows stagedstreaming to Fluree · CONNECTED
The graph builds itself.
Entities resolve, duplicates merge, and relationships infer in place — no modeling marathon, no manual ontology.
CustomerOrderProductContractOwner
Answers, with receipts.
Ask in plain language. Every answer traces back to the exact row it came from — for humans, agents, and apps alike.
NLMCPRESTSPARQLTop accounts at risk this quarter?SPARQL · GENERATEDSELECT ?acct ?arr WHERE { ?acct a fin:Account ; fin:risk "high" ; fin:arr ?arr .} ORDER BY DESC(?arr)ANSWER3 accounts at elevated riskAcme RoboticsNorthwind CoGlobex CorpTOTAL EXPOSURE$1.84M ARR exposedtraced · 4 sources
What Fluree Unlocks For Your Archive
Six capabilities no MAM, DAM, or generic-AI service gives you on its own.
Tagged against your editorial taxonomy, not “person” and “outdoor scene”
Fluree CAM tags content against YOUR controlled vocabulary, managed in ITM. A news clip isn’t “two people at a podium” — it’s tagged with the journalist’s name, the location from your geography taxonomy, the topic from your editorial taxonomy, and the series from your production database.
- Your terms, not Rekognition or Cloud Video AI defaults
- Taxonomy team owns the vocabulary, AI applies it
- Editorial standards enforced at archive-scale speed
100,000+ assets tagged in 24 hours — against your current taxonomy
Process millions of hours of legacy content through AI classification. Every asset gets entities extracted (people, places, organizations, topics), concepts mapped, and relationships linked. Content invisible for decades becomes searchable in days.
- National broadcaster case: ~500K assets, 10× knowledge growth
- Works on content that was never properly catalogued
- Tagged, governed metadata on every asset
Video, audio, text, images — one search, every result
Speech-to-text for audio, scene analysis for video, OCR for scripts and documents, visual recognition for images. Every format maps to the same controlled vocabulary in the same knowledge graph. One query returns clips, recordings, scripts, and photographs together.
- Video + audio + text + images + production documents
- Same vocabulary across every format
- Cross-format results in one view
Cross-vocabulary alignment keeps old archives searchable under new terms
When your vocabulary evolves — “Eastern Europe” becomes “Central and Eastern Europe,” “Peking” becomes “Beijing,” “Czechoslovakia” splits — ITM auto-aligns legacy tags to current taxonomy. Assets tagged with the old term become discoverable under the new one without re-tagging.
- Auto-alignment — no re-tagging projects
- Multilingual mappings included
- Vocabulary evolves continuously, not as one-time migrations
Rights status visible alongside every asset, every search
Rights metadata connects to content in the graph. Every asset links to its rights holder, license terms, territory restrictions, and talent agreements. When someone searches for content, clearance status is visible alongside the asset itself — not in a separate spreadsheet.
- Owner, restrictions, territory, expiration in one view
- Licensing decisions in minutes, not days
- Immutable audit trail of every access and reuse
Your library, queryable by AI agents natively
The enriched archive IS a knowledge graph — entities, relationships, and governed metadata ready for GraphRAG, MCP-connected agents, and conversational research. Build recommendation engines, automated highlight reels, content-aware ad insertion, and copilots that query your governed metadata.
- Native MCP + GraphRAG retrieval
- Agents query with full provenance and rights
- Archive becomes a revenue engine, not a cost center
| Capability | Traditional Manual & generic-AI |
Fluree CAM + ITM |
|---|---|---|
| Speed | Months of manual, or noisy generic-AI batches | 100,000+ assets in 24 hours |
| Vocabulary alignment | Generic labels or inconsistent manual tagging | Your controlled taxonomy, governed in ITM |
| Multi-format coverage | One format at a time, one system each | Video + audio + text + images + documents |
| Entity resolution | Not supported | Golden records — same person across every asset |
| Relationship extraction | Not supported | People, places, topics, series — all connected |
| Legacy-term alignment | Manual, or not at all | Automatic — legacy tags ↔ current taxonomy |
| Rights integration | Separate spreadsheets or systems | Connected in the graph alongside content |
| Search experience | Requires exact metadata queries | Plain English across every format |
| AI / GraphRAG ready | Not supported | Native — archive queryable by AI agents |
FAQ
Do we have to replace our existing MAM or archive system?
How is this different from generic AI tagging services?
How fast can you process our archive?
What about content tagged with outdated vocabulary?
What formats do you support?
Can we search across all formats at once?
How does this help with rights and licensing?
Can AI agents query our archive?
Recognized by Gartner