Every other recruiting CRM stores CVs and scraped data anyone can buy. Rekruit puts a real AI interview at the core: it scores each candidate, so agencies shortlist from who's actually ready and place faster.
01 — The thesis
Agencies are replacing legacy tools (Bullhorn, Loxo) with AI-native CRMs fast. But every one of them, new and old, still trades in stored and scraped data — the commodity. Rekruit is the only one where the intelligence is measured interview readiness: earned by the candidate, impossible to buy, and the thing a recruiter actually needs to know before they present someone.
Axes: legacy → AI-native against stored/scraped data → measured readiness. The whole category is moving right; only Rekruit is also at the top.
02 — The market is proven
A new AI-native CRM for agencies (anonymised as Comp1) validates the demand: it raised a $21M Series A and 10×'d revenue in a year. It proves agencies will switch for AI, but its intelligence is still scraped data. Readiness is the layer it doesn't have.
Series A
Balderton · Sept 2026
Agency customers
5,000+ daily users
Revenue growth
through 2026
Placements
reported across base
Comp1 ARR, Oct 2025 → Feb 2026
€100k to €1M in four months. This curve is the shape an acquirer prices.
03 — Target audience
Teams paid only when a candidate is placed, so knowing who is truly ready is money, not a nice-to-have. Ranked by where to start.
Paid per placement, screening dozens of candidates a week. German-language voice interviewing is a real edge most competitors lack, and readiness scoring cuts bad submissions — it pays for itself in one avoided mis-send.
Compete on shortlist quality and speed. A role-mapped readiness score lets them present fewer, stronger candidates faster than a keyword-matching ATS.
Run hiring for many clients and must prove quality-of-hire. Readiness data is a reporting and differentiation layer they can show the client.
Same readiness engine, candidate-side: institutions graded on placement outcomes. A natural second market once the agency product is proven.
Buyer ≠ user
Candidate
end user · lives in Sprich · practices free
Readiness data
scored, consented · the shared spine
Recruiter
the buyer · lives in Rekruit · pays the seat
04 — Product structure
Candidates practice in Sprich; that generates scored readiness data; recruiters act on it in Rekruit. The shared spine is the moat — a rival CRM can't buy it, because the candidate had to earn it.
Sprich · candidate
Rekruit · recruiter
Shared data spine
Every candidate practices a real interview and uploads a CV; the profile shows measured, role-mapped readiness — not keywords.
A kanban from needs-practice to placed. Each card carries the score, the top gap, and the next best action. Moves persist.
The original CV is stored, not just parsed text. Recruiters open it from the candidate record via a short-lived signed link.
Admin-provisioned recruiter orgs. Each company logs in and sees only its own cohorts and candidates. No cross-company leakage.
Invite a candidate to an interview in a click; the result lands straight back on their profile.
Let the AI screen or run a first-round interview in the browser — no phone numbers — then score it and update the profile.
What's built vs what sells the next tier
Compliance · EU AI Act
AI used to evaluate or rank job candidates is “high-risk” under the EU AI Act. Rekruit is built for that from day one: candidate consent before any profile is shared, a candidate-side framing (we measure readiness, we don't auto-reject), transparent rubric-based scoring a human can review, and EU hosting. Full legal review is on the roadmap with counsel — this is design intent, not legal advice.
05 — The workflow it drives
Scored low. The top gap is named.
Re-interviewing, score climbing.
Meets the role's competency bar.
Presented to an employer.
Hired. Outcome logged.
06 — The competitive field
The incumbent. Stores and tracks; AI is bolted on. Heavy, slow, keyword-driven. No readiness signal.
Cleaner and cheaper, with AI sourcing. Still trades in scraped contact data, not measured ability.
The closest comp: AI-native, well-funded, fast. Its intelligence is still scraped data — readiness is the layer it lacks.
Interview practice and video assessment, but stand-alone tools, not the recruiter's CRM. We put the assessment inside the pipeline.
An AI CRM where every candidate carries a real, role-calibrated readiness score — assessment built into the pipeline, not bolted on.
07 — Go-to-market
08 — Pricing
Solo
Independent recruiters
Agency
Growing desks & teams
Enterprise
Multi-office agencies & RPO
Per-seat, annual, AI bundled in (no token anxiety). The only metered add-on is heavy interview/AI-call minutes beyond the plan — the same shape the funded AI-native CRMs already charge.
09 — For the sale
Code is table stakes. The order below is the pre-listing priority — the niche and the first reference customer are the value.
A single recruitment agency running real jobs through Rekruit, with a number: fewer bad submissions, faster shortlists, or a placement won. The gatekeeper — worth more than any feature.
Candidate practice, scored profiles, jobs, and the pipeline end to end. This page is that asset.
Env-driven admin, multi-tenant, no personal data, handover docs + schema. Done.
“Every recruiting CRM stores and scrapes data. This is the one where the intelligence is measured interview readiness — earned by the candidate, impossible to buy.”