Score every applicant. Ship the reasoning to your client.
Built for agencies running 8–20 concurrent reqs with 300–1,000 applicants on the high-volume roles. Unlimited scoring on every desk, the full AI suite included — and every evaluation ships to your client as the deliverable, reasoning attached.
Sold by the desk, not the seat. A fit score you can defend.
Priced by the desk, not by the pile — the bill scales with your team, never with the candidate count. Score every applicant on every req and run the full AI suite on the keepers — all included, sized to your desks and billed annually.
Four jobs the AI actually does on a search.
- Job 01
Score the flood, then fully evaluate the keepers
Scoring reads every applicant, ranks them against the JD, and returns the reasoning behind each — the whole pile, unlimited. Pick the keepers and run the full evaluation on each, all included on your desk.
- Job 02
Ship a deliverable to the end client
Every evaluation write-up exports as a client-ready deliverable — fit scores, ranking reasoning, and an AI Evaluation on each, as a PDF or email. Generate it on as many candidates as you want.
- Job 03
Prep the interview without losing the billable hour
Interview Prep turns ten minutes of prep into a one-minute review of resume-grounded questions, included on every desk. The recovered hour goes back on a new req.
- Job 04
Run multiple clients without the context switch
Store each client’s company profile once, layer a JD-specific override on top, and every AI action runs against that stacked context. The calibration you build lives in your account, on your data — a switching cost in your favor.
How unlimited scoring maps to a real search.
| What you do | What it costs | What you get |
|---|---|---|
| Score / rank the pile | Included — unlimited | Fit score + reasoning + ranked position on every applicant, plus a clean formatted resume — the whole pile, no meter |
| Fully evaluate a candidate | Included on every desk | The full AI suite below — run it on anyone, as often as you want, no per-candidate charge |
| → AI Evaluation | included | The structured write-up you ship to the client |
| → Interview Prep | included | Resume-grounded questions, per interview |
| → Interview Analysis | included | Post-interview signal + next-step rec, against the evaluation |
Worked example
A search with 400 applicants. Score all 400 — the top sorts itself. Run the full evaluation on the eighteen worth a real look, or on all 400. The bill doesn’t move.
Plans are sold by the recruiter desk and billed annually. We size the tier to your team on the demo. See the plans.
What recruiters told us.
We sat with senior recruiters and agency operators and asked them to describe their week. Anonymous research conversations, not endorsements. The pattern was consistent.
“I went through 300 resumes and only passed 3 along.”
“500 to 1,000 resumes at any moment, for any role.”
“A colleague and I received 15,000 resumes between the two of us in 30 days.”
A recruiter reads 300 to pass 3 — almost all the work sits at the top of the funnel, unbillable. Score the 300, fully evaluate the 3 you stand behind, run the pile twice if you want. The bill is the desk, not the candidates.
Your client’s GC will ask. You’ll have the answer.
Every AI output is a recommendation to a human, never an automated decision — the human-oversight foundation that supports your team on AEDT, AIVIA, and EU AI Act exposure. Bias-audit data export is built in. Candidate AI-disclosure copy is tenant-editable for your clients’ legal teams.
What CertAIn is not.
- Not an auto-rejection engine. Built for depth on the candidates you actually consider and submit, not bulk auto-reject.
- Not an ATS. Your candidates stay in your system of record. CertAIn adds judgment on top — Greenhouse live today, Ashby and Lever on the roadmap, CSV import/export day one.
- Not a sourcer. We read candidates once you have them; we don’t find them.
- Not a scheduler. We’re the evaluation layer above scheduling.
- Not a chatbot. Every output is structured, exportable, and auditable.