All workFILE 03 / 04

Media

Document intelligence at newsroom scale

Shipped at Newsweek · led by Nikhil Bery

01

The problem

A newsroom sits on tens of millions of documents no journalist can search fast enough. The archive is an asset only if you can find the right record in seconds, not hours.

02

The constraint

Editorial work runs every day; the search and the apps around it have to stay up, stay accurate, and fit into how the newsroom already writes and publishes.

03

The system

A 30M-document search index behind 15 production AI apps: retrieval, classification, and editorial automation wired into the daily workflow instead of bolted beside it.

FIG. 01 · SYSTEM FLOW · 6 NODES · 5 FLOWS

30M-document archive → Hybrid search index (ingest). Hybrid search index → Retrieval & classification (query). Retrieval & classification → 15 editorial AI apps. 15 editorial AI apps → Editor approval (draft & route). Editor approval → Publish (approved)

04

The human in the loop

Editors keep the byline: the apps surface, draft, and route; a person approves before anything publishes.

05

The outcome

30M-document search, 15 production AI apps, and roughly 497 hours saved every 30 days.