query_stats API Evangelist Product
Insights Bundles
One account, read from both sides, for the team selling into it.
Account intelligence on a single enterprise. The demand side comes out of its own job postings, press, and blogs — every technology carrying the posting count and the matched term behind it. The supply side comes from the APIs it publishes and how they score. Then: the incumbents, the distinctive choices, the whitespace verified absent across the whole corpus rather than inferred from a sample, the org map, a peer cohort re-extracted identically, and the computed openings. Ships with the complete machine-readable data bundle.
Who buys it
The go-to-market team that has to get into that account, and needs to know what it already runs before the first call.
Know what they already run before the first call
Every other product here is bought by people who publish APIs. This one is bought by people selling into a company that does. It answers the question a go-to-market team actually has: what is this account already running, who are the incumbents, where are the genuine gaps, and what will they judge our product against?
The demand side is extracted from the account's own job postings, press, and blogs — every technology carrying the posting count and the matched term behind it, so nothing is a guess. The supply side is read from the APIs the account itself publishes and how they score. The distance between the two is where the opening usually is.
What's in every one
- What the account is buying — dozens of investment dimensions, ranked against the Fortune 1000
- The incumbents, the distinctive choices, and the stack broken out by kind
- Whitespace — targets verified absent across the full corpus, never inferred from a sample
- The org map — function, location, posting recency, platform affinity
- The peer cohort — competitors re-extracted identically, so the comparison is honest
- The supply side — published specs, provenance, and graded agent-readiness
- What the account publishes about itself
- The openings — entry points, displacement targets, and discovery questions to take into the room
Why the whitespace claims are trustworthy
A false "they don't use X" is the one error that destroys this deliverable's credibility in front of a customer, so every whitespace target is verified absent across the entire corpus rather than sampled. The complete machine-readable data bundle ships with the report, which means your team can check any claim against the source and keep interrogating it long after the first read.
What you get
The data bundle is the evidence behind every number — layered per-entity data, an APIs.json manifest, a conversation primer, and a data dictionary — packaged to drop straight into the AI tool of your choice. Converse with the research you bought, check any claim against the source, and take it further than the PDF.
5 published
JPMorgan Chase — Enterprise Insights Bundle
What JPMorgan Chase is actually buying, read from 7,799 of its own job postings — and what its API surface says back.
Salesforce — Enterprise Insights Bundle
What Salesforce is actually buying, read from 1,434 of its own job postings — and the exemplar API surface it will judge yours against.
Autodesk — Enterprise Insights Bundle
What Autodesk is actually buying, read from 632 of its own job postings — and the exemplar API surface behind it.
Splunk — Enterprise Insights Bundle
What Splunk is actually buying, read from 955 of its own job postings — and why a platform this API-heavy publishes machine-readable contracts for only three of its fo...
Adobe — Enterprise Insights Bundle
The Fortune 1000's single heaviest AI buyer, read from 1,187 of its own job postings — and the API surface behind it.
Need the account you're chasing?
Insights Bundles are built per account, primarily Fortune 100 but any enterprise with a public hiring and API surface. Name the account and it can be built.