Intelligence · distribution
Using MitchelLake intelligence data
Our principle is simple: conclusions are open, structured data is controlled, and the machinery stays ours. Cite freely; extract by agreement.
Open — no key required
Every page on this site is open for reading, sharing, citation and indexing: articles and analysis, individual signal pages on the wire, the Talent Market Index with its current reading, charts, methodology and confidence intervals, and regional and sector gauges. A public JSON summary carries the current reading for programmatic citation, and an embeddable badge shows the live reading with a link back — drop it into a story or dashboard:
<a href="https://mitchellake.com/intelligence/market-health">
<img src="https://mitchellake.com/badge.svg"
alt="MitchelLake Talent Market Index" /></a>Cite the index as “MitchelLake Talent Market Index” with a link to the instrument page, quoting readings with their confidence interval and methodology version.
Approved — free for journalism and research
Structured feeds require an access key: RSS, Atom and JSON feeds of the wire and analysis, and the full index dataset (weekly series with intervals, the readings archive, sector gauges and public-benchmark tables). Access is free for journalists, researchers, institutions and partners — request below, and we reply by email with a key and simple usage terms. Keys are tracked and revocable; the free tier is rate-limited to 60 requests an hour, which is generous for any newsroom or research use.
Use a key as ?key=mlk_… on any feed URL (feed readers) or as an Authorization: Bearer header.
Commercial — by agreement
Bulk access, deep historical data, sector / geography / company velocity feeds and advanced index components are available under commercial syndication or API agreements, with higher rate limits and support. Start with the same form and choose “Commercial”, or talk to any office via the contact page.
What we don't distribute
The index methodology is published in full on the instrument page — that transparency is deliberate. What we don't expose, at any tier, is the machinery beneath it: signal-detection and confidence-scoring internals, enrichment pipelines, raw bulk corpus data, and any linkage between signals and client outcomes beyond the aggregate statistics we publish.