For AI recruiting agents

One candidate.
Twenty-five lookalikes.
One API call.

Sourcing tools charge $1,000/mo per seat. Your agent gets the same data through an API. searchable by 30+ filters, with verified contact info and warm-intro paths.

Get an API key → See the flow

A complete sourcing loop

From "I like this person" to a shortlist in 3 calls.

①

Find lookalikes

POST /v1/find-similar-people. pass one LinkedIn URL. We extract their title, seniority, skills, and search for 25 similar people at OTHER companies.

1 + 0.8/result

②

Get the recruiter pack

POST /v1/bundles/recruiter-pack. one call gives you a candidate + 8 similar candidates + contact info, all enriched.

30 cr flat

③

Warm-intro paths

POST /v1/bundles/relationship-graph. given any candidate, returns their past coworkers + where those coworkers are now. Find mutual connections.

15 cr flat

Hiring intent triggers

Pitch when the budget is open.

Combine the live hiring feed with the buying committee. pitch your placement service before the role goes to a competitor.

`/v1/low-competition-hires`

Jobs with fewer than 25 applicants. Sortable by validThrough urgency. Your agent prioritizes contacts before the role gets flooded.

1 cr / result

`/v1/hiring-intent`

Companies actively hiring for X role + the actual hiring manager's contact info. Replaces UserGems-style tooling at 1/100th the price.

8 cr / resolved

`/v1/champion-just-moved`

Cross-reference your placed candidates against the job-change feed. When they move, you get pinged. they're your warmest re-pitch.

2 cr / resolved

Code example

Recruiter agent in 30 lines.

recruiter.py

import requests, os
H = {"Authorization": f"Bearer {os.environ['AE_KEY']}"}
AE = "https://api.agentenrich.com/v1"

# 1) Hiring manager has one candidate they love. find 25 more like them
seed = "https://www.linkedin.com/in/some-amazing-engineer"

similar = requests.post(f"{AE}/find-similar-people", headers=H,
  json={"linkedinUrl": seed, "limit": 25}).json()

# 2) Enrich each with the recruiter bundle (gets contact info too)
shortlist = []
for candidate in similar["similar_people"][:10]:
    pack = requests.post(f"{AE}/bundles/recruiter-pack", headers=H,
      json={"linkedinUrl": candidate["linkedinUrl"]}).json()
    shortlist.append(pack)

# 3) Find warm-intro paths. who do they know?
for c in shortlist:
    graph = requests.post(f"{AE}/bundles/relationship-graph", headers=H,
      json={"linkedinUrl": c["source_candidate"]["linkedinUrl"]}).json()
    c["warm_paths"] = graph["potential_warm_paths"]

# Your LLM ranks + drafts outreach for each

One candidate.Twenty-five lookalikes.One API call.