// fig. 01 — people search

People Search API
for AI agents.

800M+ verified B2B profiles, 60+ filters and 8 operators. Real-time data, verified emails, GDPR-compliant — built for AI agents, sales tools, and recruiting platforms.

↓ scale60+ filters · 8 operators
800M+// profiles
60+// filters
142ms// p50 latency
API
// figure-02 — endpoint

One endpoint. Every shape of query.

60+ columns and 8 operators (=, >, >=, <, <=, between, in, like) — combine them with AND/OR to express any ICP.

Combine current_company, years_of_experience and skill with =, >= and in operators.

POST/v1/people/search
// 03 · request
{
  "filters": {
    "op": "and",
    "conditions": [
      {
        "column": "current_company",
        "type": "in",
        "value": ["Google", "Meta", "Amazon", "Apple", "Netflix"]
      },
      {
        "column": "current_title",
        "type": "like",
        "value": "Senior"
      },
      {
        "column": "years_of_experience",
        "type": ">=",
        "value": 8
      },
      {
        "column": "skill",
        "type": "in",
        "value": ["Python", "Go", "Distributed Systems"]
      }
    ]
  },
  "offset": 0,
  "count": 100
}
200OK · application/json
// 04 · response
{
  "total": 12480,
  "offset": 0,
  "count": 1,
  "credits_used": 1,
  "results": [
    {
      "id": "prof_PVURNGJihYludzaOwFCAwNajijSHFi6H0L9R",
      "first_name": "Sarah",
      "last_name": "Martinez",
      "headline": "Senior Software Engineer at Google | Cloud Infrastructure",
      "location": "San Francisco Bay Area, California",
      "country": "US",
      "follower_count": 4200,
      "experience": [
        {
          "company": { "name": "Google", "size": "10001+" },
          "title": "Senior Software Engineer",
          "years_at_company": 4,
          "is_current": true
        }
      ],
      "education": [
        {
          "school": { "name": "Stanford University" },
          "degree": "MS",
          "field_of_study": "Computer Science"
        }
      ],
      "skills": ["Python", "Go", "Kubernetes", "GCP", "Distributed Systems"],
      "years_of_experience": 9
    }
  ]
}
Filters
// capabilities

Find people the way humans do

By who they worked with, where they studied, and what they ship today. One endpoint, 60+ columns, 8 operators — wired into LangChain, MCP, OpenAI function calling.

// fig. 05─ ─ ─

Hand your agent the right buyer in one call

One endpoint returns the exact decision maker — by company, title, size, funding stage and tenure.

POST /people/search → buyers
current_title like "VP Sales"funding_stage = series_bsize in [201-500, 501-1000]

VP of Sales · Stripe

VP Sales · Series B SaaS

Match

Head of Sales · Notion

Head of Sales · 201-500

Match

VP RevOps · Figma

VP RevOps · Series B

Match
Matches12,480 buyers
// fig. 06─ ─ ─

Stream live ICPs straight into your AI SDR

Stack country, industry and influence signals so your agent refreshes prospect lists at runtime — not from a static CSV exported in March.

agent.search(filters)
profile_country in [US, UK, CA]3.2M
profile_industry like Software412k
follower_count >= 1000184k
keyword like AI82k
Final list returned to agent
Matches82,410 prospects
// fig. 07─ ─ ─

Surface candidates with the right track record

Past companies and top schools — your sourcing agent finds ex-FAANG, ex-Big4 and Ivy/MIT graduates in one query.

past_company / school · in [...]

McKinsey & Company

Engagement Manager · 4 yrs

past_company

Bain & Company

Associate · 2 yrs

past_company

Stanford University

MS · Computer Science

school

MIT

PhD · AI

school
Matches9,820 candidates
// fig. 08─ ─ ─

Pre-qualify on skills and credentials

Your agent filters on tech stack and certifications in the same call — only credible profiles ever reach your sequences.

skill · in / certification · like
PythonMachine LearningAWS Certified Solutions ArchitectKubernetesPMPTypeScriptGCP ProfessionalPyTorchCISSPGoCFA Level IIIDistributed SystemsScrum MasterTerraform
Matches58,210 specialists
Coverage
// fig. 10 — coverage

Source data across 20+ points

Continuous global refresh from public sources — not a stale quarterly snapshot. Profiles, companies, and contact data verified in real time.

// dataset · global feed20+ points
// sources
20+
// refresh
live
// regions
global
Delivery
// fig. 11 — delivery

Data delivered where your stack lives.

Same dataset, three transports. Pull it via REST, plug it into your agent through MCP, or stream changes to your webhook in real time.

// fig. 11REST
// channel

API

Pull on demand.

One JSON request. 60+ columns. 8 operators. Authenticate with a Bearer token, point at the endpoint, get verified data back in 142ms (p50).

POST/v1/people/search
// notes
  • Bearer auth
  • JSON in, JSON out
// fig. 12AGENT
// channel

MCP

Native tools for agents.

Drop our MCP server into Claude, Cursor, or any agent runtime. The model picks the tool, builds the filters and reads the response — no glue code, no schemas to maintain.

TOOLsearch_people · enrich_profile
// notes
  • Claude · OpenAI · Cursor
  • tool-call native
  • no schema babysitting
// fig. 13PUSH
// channel

Webhooks

Get notified the moment it changes.

Subscribe to ICP events — new matches, role changes, funding rounds. We POST to your endpoint with the delta. Your sequence reacts before the data goes stale.

POST→ your_endpoint
// notes
  • ICP delta events
  • signed payloads
  • exponential retry
Use Cases
// fig. 14 — build surface

What can you build with our API.

One POST request, four product surfaces. Each layered on top of the same endpoint — only the question changes.

// fig. 15sourcing copilots

AI Recruiting product

Past employers, top schools, degrees, certifications and tenure in the same payload. Your agent shortlists ex-FAANG, ex-Big4 and Ivy/MIT graduates — and the data refreshes itself.

// filters
past_companyschooldegree_levelskillcertificationyears_of_experience
// outputranked shortlist → ATS
// fig. 16outbound agents

AI SDR

Wire funding triggers and ICP filters into your agent. Stream verified profiles into the sequence. Re-query when the ICP changes — the agent owns the list, not a CSV exported in March.

// filters
current_company_funding_stagecurrent_titlecurrent_company_sizeprofile_countryis_currently_employed
// outputlive prospect feed → sequence
// fig. 17deal sourcing

Investment platform

Catch stealth founders, track investor overlap, funding stage and tenure across thousands of operators. Pipe raw JSON into your scoring model — no scrapers, no stale lists, no broken refresh jobs.

// filters
current_title ~ "Stealth Founder"current_company_investorcurrent_company_funding_stagecurrent_company_sizeyears_at_current_companycurrent_company_industry
// outputscored deal flow → analyst stack
// fig. 18embedded data layer

Sales automation platform

Power people search, enrichment and ICP refresh inside your product — one endpoint, MCP-ready, GDPR-compliant. Stop maintaining brittle scrapers; ship the feature instead.

// filters
current_companycurrent_titlecurrent_company_categorylanguage_proficiencyfollower_count
// outputembedded search → your app

Building something we haven't listed? Tell us what you're wiring it into. Half the columns we ship today came from a customer asking for one.

Compliance
GDPR Logo

GDPR compliant

Full compliance with European data protection regulations. Your data privacy is our priority.

CCPA Logo

CCPA compliant

Adhering to California Consumer Privacy Act standards for maximum data protection.

Publicly available data

All data sourced from publicly available and verified sources, ensuring ethical collection.

Related
Get Started
// fig. ∞ — ship

Build with us. Now.

Get an API key in 60 seconds. Plug your AI agent into 800M+ verified profiles and 75M+ companies — today.

↓ nextREST · MCP · Webhooks