1B+ person profiles — professional, decision-maker, developer and healthcare — plus 60M+ companies and the signals that show what changed. One integration, kept current, so your team ships the data feature instead of running the data operation.
Platforms shipping their own products on these records today.
Most providers stop at the professional profile. The three layers under it are where products get built that nobody else can build — and all four ship together in the People Dataset.
Verified work history, titles, employers and education. The base layer — and the one every provider has.
Curated and continuously monitored, at any company you name. 10M+ of them sit across the top 250K companies.
GitHub profiles and real developer activity — which engineers already use your stack, rather than who filled in a form.
Doctors, nurses and residents — the clinicians a commercial team needs to reach, and the ones who shape what a field believes.
Structure, leadership, funding and filings — and what moved this week.
Activity sits on the person record, so you get what someone is saying, not only what they are.
Every one of them reads the same graph. The difference is what you hand it, and how much of the answer you want at once.
Find the people who match your criteria — not the ones you already know about.
A name, a profile URL or a work email in. A complete person out.
Build the account list from what companies are doing now, not last quarter.
Firmographics, leadership, funding — and what changed this week.
45M+ of them. Ask who they are at a company, or whether one person is one.
What the people you track are actually saying, and who engaged.
Get told the moment something changes, instead of re-checking.
People who told a staffing partner they are looking — about 1.5M added every month.
1B+ profiles, including the decision-maker, developer and healthcare segments, on your schedule.
60M+ companies and their firmographics, delivered in volume.
Most teams run an API and a bulk feed together — the files for scale, the API to keep the records that move.
Resolve at the moment of decision, so a call returns what is true now rather than what was true when a file was cut.
Volume without per-call cost. You agree the cadence; the files arrive on it.
The same products inside Claude and ChatGPT, and any other tool that speaks them.
A visual layer over the same APIs. Run real queries against real records in a UI before anyone writes code.
The part that decides whether your feature is trusted: what happens before the data reaches you.
These are the shapes teams ship most often. The graph does not change between them — only which parts you ask for.
A closed-won contact leaves a customer — that is churn risk. They land somewhere new — that is a warm lead. Decision Makers plus change signals turn both into an alert instead of a quarterly surprise.
Revenue teams keep target accounts and buying committees current, and hear what decision makers in a segment are saying.
Refreshed on your schedule
Contact and account decay stops at the source. One integration instead of a quarterly cleanup project.
Worked in payments · Northwind · 2019–2022
Track where skills and people move across industries and geographies, and keep candidate records current without re-sourcing.
Surfaced as they happen
Validate a target’s leadership, funding history and filings before the first call — and see leadership moves as they happen.
resolve(“a••••@example.com”)
Session 2 · six weeks later
Ground agents and copilots in current person and company context, by API or inside Claude and ChatGPT.
Public developer activity
Vertex Labs · 7 engineers on your stack
Find the organisations whose engineers already use your stack. The signal is real developer activity, not a form fill.
Teams building their own prospecting, routing and account planning rather than paying per seat for someone else’s. You own the tool and the workflow; we are the data layer underneath it.
We resolve and validate our own graph rather than reselling someone else’s, and matching stays hashed — so the raw identifiers you send are never exposed.
Security & Trust Centre
EU & UK
California
Audited
Identity, full work history with dates and role descriptions, education, and public social activity. Where someone is a developer or a healthcare professional, the attributes specific to that community come with the record.
Yes — 95M+ GitHub profiles and real developer activity. It is how dev-tools teams find the organisations whose engineers already use their stack, instead of waiting for a form fill.
Signals tell you. Role changes, company moves, leadership changes, funding and hiring arrive as signals, so you act on the change rather than discovering it at the next refresh.
Yes. Ember is a free, self-serve sign-up — a UI over the same APIs — so your team can run real queries against real records before anyone writes code.
API when freshness at the moment of decision matters. Bulk when volume matters. Most teams run both and use the API to keep the records that move.
One endpoint and a key. The longer part is usually deciding which attributes you want, not wiring it up.
Fifteen minutes to find out whether the graph fits it, and what the records would actually look like on your data.