One engine aggregates the records a market produces, scores them, and returns a one-line reason for every match, over REST and over MCP. The legal Hiring Index is the proven flagship that is live today: roughly 1,200 firm dossiers and 1,775 feeds on a 47-node taxonomy, refreshed nightly. The same endpoints and the same tools re-point to logistics, healthcare, manufacturing, or any market that needs aggregated data with matching reasoning.
The structured-data layer for legal hiring: every firm, posting, and (soon) lateral move on one taxonomy, with a confidence score and source citation on every record.
# Python · query the Hiring Index import httpx, os r = httpx.get( "https://api.placement.solutions/v1/jobs", params={"industry": "legal", "state": "NY", "limit": 5}, headers={"Authorization": f"Bearer {os.environ['PS_TOKEN']}"}, ) print(r.json()["data"][0])
# cURL curl https://api.placement.solutions/v1/jobs?industry=legal&state=NY&limit=5 \ -H "Authorization: Bearer $PS_TOKEN"
// Node 20+ · global fetch const res = await fetch( "https://api.placement.solutions/v1/jobs?industry=legal&state=NY&limit=5", { headers: { Authorization: `Bearer ${process.env.PS_TOKEN}` } }, ); console.log((await res.json()).data[0]);
{ "object": "list", "data": [ { "object": "job", "id": "harv_2d129d1498f7", "title": "Litigation Associate", "company": "Greenberg Traurig", "location": "New York, NY", "state": "NY", "industry": "legal", "role_type": "associate", "salary_min": null, "salary_max": null, "date_posted": "2026-05-28", "is_law_firm": true, "url": "https://gtlaw.wd1.myworkdayjobs.com/...", "created_at": "2026-05-28 12:18:59" } ], "next_cursor": "eyJhIjoiMjAyNi0wNS0yOCJ9", "limit": 5 }
A three-engineer scraping team runs $234K to $510K a year, loaded, and takes six months to reach stable output before the anti-bot arms race even starts.Our entry tier is a fraction of one of those salaries, and you integrate in a week.
Legal media and CI desks, AmLaw BD and competitive intelligence, executive search research, litigation finance underwriting, strategy consultancies, and LPL insurance carriers who need legal hiring data as structured rows, not PDFs.
Looking for general B2B contact records across every industry, individual recruiter seat licenses, or a candidate sourcing tool. We are a legal-sector data feed, not a contact database or an ATS.
Daily REST pulls into your warehouse, signed webhooks into your CRM or underwriting model, or a quarterly co-branded snapshot published under your masthead. Bearer-token access on approval.
SOC 2 Type 1 audit targeted for 2026 Q4, Type 2 to follow. Current controls and our security whitepaper are available under NDA on request.
Hosted on ISO 27001-certified infrastructure with US-only data residency. Subprocessor list available on request.
We do not train on customer queries or returned data. Subprocessor list public and versioned.
We publish the roadmap because the legal sector does not reward vendors who blur the line between shipping and aspiration. The methodology page is always the canonical version of what a record means and when it lands.
We would rather have ten teams shaping the schema than a wall of logos. The jobs and firm datasets are live in production today; the movement layer is rolling out with these partners. Pilot quotes are in review, and we are not posting customer logos until partners are in production and have cleared us to. Design partners get founding pricing locked for the life of the contract, a direct line to the people building the feed, and first call on the lateral-movement endpoints as they ship.
Pre-launch. Postings and firm dossiers are live; the movement layer is rolling out to this cohort first.
placement.solutions is a data-aggregation and matching-reasoning API from CestoneAI: it ingests public and operator data, scores it with explainable matching, and delivers records over REST with signed webhooks. Its flagship dataset is the legal Hiring Index - AmLaw 200 hiring-intelligence feeds, lateral-move tracking, real-time job-posting webhooks, and firm headcount for underwriters, refreshed daily, and the same engine re-points to any market that needs aggregated data with matching reasoning. Teams reach for it when horizontal data vendors don't expose the record type or cadence they need.