in
LinkedIn leads
Live · enriching ~3,800 profiles / hour right now

Every LinkedIn profile,
fully enriched.

Paste a URL. Get back the full picture: verified email, phone number, work history, education, skills, certifications, and more. Built for sales, recruiting, and AI agents who need the truth — not what someone half-finished on their profile.

No subscription — pay in Ounie credits≈3 seconds per profileCSV · JSON · webhook · MCP · x402
● live enrichment248 profiles · 18s
$ curl /api/scrape
profile_urls=[
"linkedin.com/in/abrar",
"linkedin.com/in/rita"
]
How it works

From a list of URLs to a clean dataset in three steps.

1

Paste your profile URLs

Drop a list of LinkedIn profile URLs (linkedin.com/in/<slug>) — one or 5,000 at a time. We dedupe, canonicalize, and skip the ones we can't crawl before you spend a credit.

2

We enrich each profile

Job lands in a queue. We extract verified email, phone, work history, education, skills, certifications, and more. Live progress; close the tab and we'll fire a webhook (or email) when it's done.

3

Export anywhere

Download as CSV or JSON, fire a webhook into your CRM, or hit the REST/MCP/x402 API. The dataset is yours — no DRM, no usage cap on what you've already paid for.

What you get back

Twenty-plus fields per profile. Clean. Normalized. Queryable.

Every row is the same shape no matter who you searched for. Phone numbers are normalized to E.164. Work history comes back as structured roles (title, company, dates, location, description) — not a free-text string a regex won't survive. Education, skills, certifications, and languages each have their own array.

22+
Fields per profile
5,000
Profiles per job
≈3s
Per profile
99.4%
Schema fidelity
Verified email
Phone numbers
Full work history
Education + degrees
Skills (ranked)
Certifications
Languages spoken
Current company + industry
City, region, country
Connections + followers
Personal websites + Twitter
Awards, projects, publications
Webhooks on job complete
Native MCP server
REST + x402 API
Use cases

From "I need 500 enriched leads by Friday" to "this is our weekly data feed."

One enricher, six workflows, one queryable dataset. Most teams start with outbound and end up running four of these at once.

Outbound sales

Build qualified prospect lists in minutes. Pull verified email + direct phone + current role for every Head of Sales at a Series-B fintech, every CTO at a Boston biotech, every VP Marketing in your ICP — straight from the LinkedIn URL.

≈1,000 SDR-ready rows / hour

Recruiting + talent ops

Sourcing pipelines stop guessing. Get the full work history, education, and skills behind each LinkedIn URL — plus a verified email so your reach-out actually lands in their inbox instead of an InMail black hole.

decision-makers, not just titles

Market & talent intel

Map competitors' hiring patterns. Track where senior engineers leave Stripe for, which schools dominate a vertical, what skill stacks command which titles. Schedule weekly re-scrapes so the dataset stays fresh.

weekly diffs by company or school

Investor research

Vet founders, ops hires, and board candidates with a single URL. Past roles, tenure, exits, education, certifications. Build a clean diligence dossier in seconds instead of clicking through a LinkedIn screen reader.

one URL → full dossier

AI agents

Plug the MCP server straight into Cursor, Claude, ChatGPT, or your own agent. The model calls scrape_linkedin_profiles, polls until done, and exports the rows — no glue code. Or pay-per-call via x402 for one-offs.

MCP + x402, agent-native

Research workflows

Replace manual profile clicking with repeatable jobs. Save a list of URLs, queue weekly enrichments, pipe results into your warehouse via webhook. The dataset stays current; the work stops.

webhook → Snowflake / BigQuery
For developers & AI agents

REST, MCP, webhook, or pay-per-call x402.

Ounie accounts get a REST API with bearer-token auth and a native MCP server that drops into Cursor, Claude, ChatGPT, or the AI SDK — your assistant can enrich, poll, and export without writing any glue. One-off scripts can hit our x402 endpoint and pay per request in USDC. Same data, same schema.

MCPCursor · Claude · ChatGPT · AI SDK
RESTBearer token, webhooks, CSV/JSON
x402USDC on Base, no account
DashboardPoint-and-click UI
// One request. Async job. Webhook or poll for results.
const res = await fetch("https://linkedin.ounie.com/api/scrape", {
  method: "POST",
  headers: {
    "Authorization": "Bearer ${API_KEY}",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    profile_urls: [
      "https://www.linkedin.com/in/abrar-kim",
      "https://www.linkedin.com/in/rita-jensen",
    ],
    label: "Q3 outbound · founders",
  }),
});

const { job_id } = await res.json();
// → poll /api/jobs/${job_id} or wait on the webhook
Pricing

Pay for profiles. Not seats, not setup, not surprises.

One profile scrape costs 5 Ounie credits — the same wallet every Ounie product shares. You are only charged for profiles actually returned; unused reserves refund automatically. AI agents can skip the account entirely and pay per call in USDC via x402.

FAQ

The questions we get on the first call.

We pull data from public profile pages — the same surface anyone can see in a logged-out browser. The legal framework around scraping public data (hiQ v. LinkedIn, Meta v. Bright Data) treats publicly accessible information as fair game. We don't bypass auth, don't pull private connections, don't republish anything proprietary. You are responsible for how you use the data — CAN-SPAM, GDPR, CCPA all still apply to your outreach.

Sign in with Ounie, enrich your first list in 90 seconds.

Pay for profiles in credits, not seats. No subscription — keep every row you've already pulled.