Search by context
Find stories by meaning and relevance, not exact words.
ConsultancyArchive vectorisation
Archive IntelligenceDecades of reporting, searchable by meaning.
Archive Intelligence turns a publisher’s archive into a governed vector database, so stories can be found by meaning rather than keywords, in any language. It is the first step of any newsroom AI journey: grounded answers, related-story context, recommendations and a licensable asset.
- Category
- Archive & AI readiness
- Type
- Consultancy
- Covers
- Model choice, cost estimate before spend, rights governance
The problem
Why Archive Intelligence exists
Archives hold a publication’s most valuable reporting, locked behind keyword search, legacy fonts and scanned pages. AI tools can’t use what they can’t find.
How it works
How vectorisation works
01
Split
Every story is split into meaningful passages.
1 / 7
What you get
Built for how desks actually work
Grounded answers
Answers written only from your reporting, with links.
Context on every story
Related coverage surfaces automatically.
Photo search
Find archive photos by description.
A licensable asset
License to AI companies on your terms.
On your servers
Governed storage that can run on your own infrastructure.
Questions
Archive Intelligence, answered
Last updated
Why start with the archive?
Every newsroom AI tool, from grounded answers to recommendations, works better on a clean, vectorised archive. It is the first step of any AI journey.
Can the data stay on our servers?
Yes. The vector database can run on your own infrastructure, with access and rights governance.
Works well with
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See Archive Intelligence on your own workflow.
Tell us what slows your desk down. We’ll show you a working demo on your own sources, then put scope, cost and timeline in writing.