200M+
Verified B2B contacts
34M+
Companies profiled
42K
Technology products, 1B+ associations
60M
US personal mobiles, deterministically linked
18+
Years first-party data
Six layers, one verified person at the center
Every feed and every integration is built from the same layers, which is why the same asset works for a marketplace, an identity graph, and a measurement product.
Contact graph
Verified B2B contacts
Name, title, function, seniority, verified work email, direct dials. Human-verified records re-verified every 90 days.
globally, about 70M US
Firmographic
Company intelligence
Domain, revenue, employee count, industry. Deliberately B2B-only.
Companies19M / 15M
US / international
Technographic
Technology install data
Confidence tiers and first and last verified dates per install.
Products1B+
Tech associations
Intent signal
PredictiveIntent
60,000+ topics captured at the source: 3,200+ US conferences, 1,000+ webinars a day, a B2B-filtered bitstream, and a patented buying-committee filter.
ahead of conventional intent, refreshed every two weeks
Signals
Company-level triggers
Funding, M&A, hiring, leadership changes, product launches. Catch buyers at the moment that predicts the need.
Signal categories
Identity Bridge
Person-to-personal linkage
Personal mobiles and emails deterministically linked to verified business identities, with probabilistic methods extending reach. No MAIDs required, so reach does not depend on deprecating mobile ad IDs.
US personal mobiles40M
Personal emails globally
Nothing reaches production from a single source. Every element is corroborated across public, proprietary, and partner sources; a dedicated research team re-verifies contacts every 90 days; the full dataset is reprocessed monthly and records that no longer clear thresholds are removed.
The source advantage
Conference network
3,200+ US conferences
Captured through our proprietary event and badge-scanning network: in-person buying intent at the point of engagement.
Webinar activity
1,000+ webinars a day
Ingested and attributed to verified B2B professionals, a direct signal of active research.
B2B-filtered bitstream
Research activity, filtered to buyers
A patented buying-committee filter strips non-buyer noise and surfaces parallel activity from the technology leaders at the same company.
What partners build with the data
Identity and measurement platforms
B2B identity spine and truth set
The verified contact and company graph as the B2B person layer inside your identity resolution or measurement products, covering the roles a consumer graph misses.
DSPs, SSPs and curation platforms
Verified B2B data layer
Firmographic, technographic, and intent attributes delivered into your pipes for curation and targeting, with person-level resolution behind every segment.
Data marketplaces
B2B audience and data layer for buyers
Your buyers query against 34M+ companies and 200M+ contacts without building a proprietary graph. Pairs with the Audience Library catalog.
Enterprise data teams
The graph inside your own graph
Feeds and enrichment for brands and enterprises licensing the verified B2B person layer on their own terms, delivered to your warehouse.
Three ways to take the data
01
File-based delivery
Structured export matched to your identity spine: contacts, firmographics, technographics, delivered on an agreed cadence. The lowest-friction path for identity graph, truth set, and enrichment partnerships.
02
Warehouse-native access
Snowflake private listings: in-warehouse access with no files or APIs to manage. Monthly full refresh standard.
03
Syndicated audiences
Prefer segments over raw data? The AdsIntel Audience Library syndicates the catalog into your taxonomy. See AdsIntel Audiences.
NDA, then a real number on your data.
01
NDA and data dictionary exchange
We share the card; you share your universe.
02
Diagnostic match test
About two weeks, on your data. No match rates quoted in advance; the test produces the number.
03
Commercial framework
Syndication, licensing, or both, shaped by what the test shows.
Let's run the test on your data
We don’t quote match rates in advance. After an NDA and a data dictionary exchange, a time-boxed diagnostic match test runs against your universe and produces the number that matters, on your data, not a rate card.
ICP Analysis & Lookalike Modeling
Buying Signals & Intent
SalesIntel Platform
Marketing
Sales
Revenue Operations
Advertising
Events

