Data//People Data

The people data API for teams shipping to production.

Structured B2B profiles with job title, work history, education, skills, and more. Verified, matched with a strict no-false-positives policy so your product does not inherit our uncertainty.

1B+
profiles collected, 450M highly verified
70%+
identity match rate
99.3%
verified work-email accuracy
200M
profile refreshes per month
//Data points

What a person record contains

One request returns all eleven categories in the same JSON shape, so your integration never has to branch on which fields showed up. Anything we could not verify comes back null rather than a filled-in guess, and your product picks the fields it actually needs.

01IdentityFull name, primary identifiers, and canonical profile references. The single anchor every other field hangs off.
02Job & CompanyCurrent title, seniority, department, and the company the person works at right now, with firmographic context attached.
03Work ExperienceFull career history in chronological order, including role, company, dates, and tenure per position.
04LocationCurrent city, region, country, and time zone where available, plus prior locations attached to previous roles.
05Email AddressesVerified work emails with per-address validation status and a confidence score, not just a syntactic check.
06Phone NumbersDirect and switchboard numbers where sourced legitimately, each with validation status.
07EducationDegrees, institutions, fields of study, and dates, so you can filter by academic background or credential.
08SkillsSelf-declared and inferred skills attached to the profile, useful for talent search and audience segmentation.
09LanguagesSpoken and written languages with proficiency where available.
10Professional ProfileBio, summary, and long-form professional context taken from public work-oriented sources.
11Network SignalsRecent activity, role changes, and other movement signals that flag when a profile is due for a re-fetch.
200 OKGET /v2/person
{
  "id": "rc_p_4f8a1c",
  "fullName": "Satya Nadella",
  "headline": "Chairman and CEO at Microsoft",
  "location": { "city": "Redmond", "country": "US" },
  "job": {
    "title": "Chairman & CEO",
    "company": "Microsoft",
    "companyDomain": "microsoft.com",
    "startDate": "2014-02"
  },
  "emails": [{ "value": "satya@microsoft.com", "status": "verified" }],
  "experience": [ … 8 roles ],
  "education":  [ … 3 schools ],
  "skills": ["Cloud", "Leadership", …],
  "network": { "followers": 11200000, "openToWork": false },
  "lastUpdated": "2026-08-30T14:02:11Z"
}
//Quality

What runs on every record before we return it

Before a profile leaves our system, it clears identity resolution against a confidence threshold, is compared to its previous version for consistency, and passes bot and fake profile filters. Emails and phone numbers run through real-time validation on the same request, so the response you receive has already survived every check we apply.

Read our Data Quality Standard →
FreshnessEvery profile carries a last-updated timestamp in its payload. Your integration can read that field and decide, per record, whether the cached version is fresh enough or a live re-fetch is worth the extra latency.
Resolution Choose cache or live retrieval on a per-request basis. The endpoint stays the same, and the response shape stays the same. You are only changing whether we return the last stored version or resolve the person again in real time.
FilteringDuplicate records, dormant profiles, and known bot patterns are stripped upstream. You receive the current, active version of the person rather than a merge candidate you have to sort out later in your own pipeline.
BillingIf no verified match comes back, no credit is charged. The null-return safeguard runs at both the data layer and the invoice layer, so a strict precision setting does not carry a hidden cost.
//Use cases

Where the people data API earns its keep

Four integration patterns that show up on almost every call with a data team building on the API. For each one, the endpoint they reach for, the fields they lean on, and what changes inside the product on the other side.

Sales productsenrich · search · email

Convert a signup into a scored, contactable lead before your first outreach.

When a prospect drops a work email or a social URL into your product, one API call resolves them into a full profile your scoring logic can read. Only when the lead clears your threshold do you spend a credit on a verified contact detail, so verification cost tracks intent rather than volume.

Job and company as the primary scoring inputs
Email Addresses with per-address confidence
Network Signals to detect buying committee membership
Fewer bounces, faster speed-to-lead.See use case →
Recruiting productssearch · social · enrich

Build talent pipelines on structured career data your matching model can actually rank.

The Search endpoint returns a ranked list from the filters your product already exposes to recruiters. A follow-up Enrichment call pulls the full career record for anyone shortlisted, so your matching model reasons over real fields rather than parsed resume text.
Structured pipelines your model can score reliably.

Work Experience tenure per role
Skills and Languages exposed as filtered facets in your UI
Education for credential-based matching
Shortlists built on facts, not keywords.See use case →
CRM enrichmentenrich · webhooks

Push clean, current contact data into your CRM without a nightly batch job.

Subscribe to webhooks and your CRM receives an enrichment payload the moment a record needs it or a person changes roles. Your merge logic handles the incoming data against your own deduplication rules, and the pipeline stays current without anyone opening a spreadsheet after hours.
A pipeline that runs itself while your ops team sleeps.

Identity fields to merge on a stable person's ID
Job and company to fill the highest-value gaps
Last-updated timestamp as your re-fetch retrigger
A CRM your reps actually trust.See use case →
AI productsenrich · MCP

Ground your agent stack in verified person context before the model reasons over it.

Serve the API through an MCP endpoint and any assistant in your stack can request a person record on demand. Every response carries a confidence score, so your agent branches on precision instead of treating every returned answer as equally trustworthy.
Confidence-gated reasoning that stops before it hallucinates.

Professional Profile as primary context payload
Confidence score to match agewnts behaviour
null return so the model kniws when to stop reasoning
Agents that act on facts.See use case →

Trusted by data-driven teams

Rated 4.6 out of 5 from 107 reviews on G2

“Our data team built an internal ops product with Reverse Contact. It improved identity resolution across systems and provided a reliable people & company layer.”

Ethan Carter
Data Team, Gitpod

“We use Reverse Contact as a trusted data provider for our product inside our RevOps workflows. It helps our customers unify CRM records and enrich missing context...”

David Bromberg
CEO, Lantern

“Reverse Contact provided a reliable identity resolution layer for our product. The API is straightforward, outputs are consistent, and match quality is strong.”

Lucas Perret
Head of Product, lemlist

Compliant by design. Defensible on request.

Reverse Contact is built on B2B open-source intelligence, with GDPR- and CCPA-aligned data practices, clear sourcing principles, and full respect for data subject rights. Your legal team can review the full posture through the Trust Center.

GDPR
CCPA

Frequently Asked Questions

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Ship people data your product can trust

Access verified B2B profiles through one API. Real-time, bulk, or async, at production scale.

1
B+
Profiles
300
M
Requests / month
500
ms
Response time (P95)