calhire
Every applicant arrives assessed and AI-interviewed.See how

Features

A complete, resume-free hiring platform

From proving skills to a consented hire — every step is verified, anonymous-first, fair, and auditable.

The platform

Everything hiring needs, rebuilt around proof

Eight capabilities work together to make hiring verified, anonymous-first, fair, and fast.

  • Verified skills profile

    An assessment built to detect cheating replaces the résumé with a portable, verified composite score.

  • Anonymous-first evaluation

    Talent is evaluated on skills only; identity is revealed on mutual consent.

  • Blind talent ranking

    Composite-score ranking on ability, with no name, photo, school, or past company in the mix.

  • Human-in-the-loop decisions

    AI recommends and explains; a person makes — and is recorded for — every decision.

  • Zero-ghosting report cards

    Every applicant gets a growth-framed report card. The word “rejected” never appears.

  • Assessment integrity layer

    A photo identity check that only people compare, plus paste blocking and behavior signals, routes risk to a human, never an auto-fail.

  • Compliance-native hiring records

    Designed for the EU AI Act, NYC LL 144, EEOC, and UAE Emiratization.

  • ATS, SSO and webhook integration

    Webhooks, SSO and ATS sync, with API access coming soon — privacy boundaries hold across integrations.

Prove it once

A verified skills profile, not a résumé

Talent takes one vetted assessment built to detect cheating: an AI text interview and, for technical roles, a two-task coding round with questions about their own code. It earns a vetted score that is explainable, time-stamped, valid for a set period, and portable across every application.

  • Technical: AI interview 40% and coding 60%. Non-technical: AI interview 100%
  • Freshness badge and a retake cooldown
  • No “résumé match” component, ever

Verified skills score

Medical Coder · Reused for every application

Score 88 · Sample
ICD-10 codingCPT codingClinical documentation

Evaluate blind

Anonymous until you both decide

Every talent is born anonymous. Companies see verified scores and skills, never a name, photo, age, school, or past company. Identity and right-to-work details unlock only when a company advances a talent and the talent consents, for that one company, logged immutably.

  • Opaque talent handles, never derived from PII
  • Consented, per-company reveal at allowed stages
  • Every reveal recorded in an immutable ledger
Anonymous pipelineSample Verified
  • 90Talent F1T6Backend Engineer
  • 88Talent A7F3Account Executive
  • 75Talent B4M1Operations Coordinator

Decide fairly

Ranked by ability, decided by a human

Verified talent is ranked on a job score you can shape: the vetted score, the job’s own interview and the match with the role. Below-threshold applicants are flagged for human review, never auto-rejected. AI recommends and explains; a person makes the call and is recorded against it, satisfying human-oversight requirements.

  • No code path can auto-reject a talent
  • Custom job-score weights per job
  • Explainable recommendations tied to the deciding human
Report cardSampleGrowth-framed

Operations Coordinator

  • Strong: Process mapping, vendor management
  • Grow: demand planning (+7 to reach the next band)
  • Next: a tailored practice set

Protect identity

No PII ever reaches a model

Anonymity is a hard architectural boundary, not a setting. Personal information is stripped before any AI sees a talent profile, across scoring, the text interview, the coding round and ranking. The integrity layer records paste, focus and timing signals, never invasive webcam proctoring: the only photos are a selfie at the start and two during the AI interview, compared by people, never by a model.

  • PII stripped at a hard boundary before any model
  • Text-only AI interview; video is human-only
  • Config-driven, swappable AI providers per task
Anonymization boundary
Name, photo, school Stripped
Verified skills & score To model

Platform & security

Enterprise-grade under the hood

The controls and infrastructure that make verified, anonymous-first hiring production-ready.

  • Multi-region & residency

    Pin data to the EU, India, or the UAE to meet GDPR, DPDP, and PDPL.

  • SAML SSO & scoped roles

    Single sign-on, IP allow-listing, and RBAC + ABAC enforced server-side. The pricing page lists which plans include each.

  • Webhooks, ATS & API (coming soon)

    Connect hiring to your stack; identity syncs only after a consented reveal.

  • Audit & compliance console

    Immutable logs, bias-audit exports, and Emiratization quota reporting.

  • Fast & accessible

    Pre-rendered, Core-Web-Vitals-tuned pages with AA accessibility throughout.

  • Notifications & email

    Reliable, templated transactional email with consented marketing only.

Feature questions, answered

How the verified, anonymous-first model works in practice.

How is the verified skills score calculated?
The vetted score blends the AI text interview and, for technical roles, the coding round: AI interview 40% and coding 60% on the technical track, the AI interview alone on the non-technical one. On each job, companies rank by a job score of the vetted score 35%, the job’s own interview 40% and the match with the role 25% by default, adjustable per job. There is no résumé-match component.
How do you detect cheating without invasive proctoring?
The integrity layer combines a photo identity check (a selfie at the start and two photos during the AI interview, compared only by people), questions and coding problems generated for each sitting, and signals such as paste, focus changes and response timing. Coding follow-ups ask about the talent’s own code. Signals route to a human reviewer rather than an automatic verdict. There is no video recording and no face analysis.
Can the platform reject talent automatically?
No. No code path can auto-reject anyone. Below-threshold talent is flagged for human review, and a person makes every person-affecting decision and is recorded as making it.
When is a talent’s identity revealed?
Only when a company advances the talent to an allowed stage and the talent consents. Identity and right-to-work details then unlock for that one company, recorded in an immutable ledger.
Which integrations are available?
CalHire offers ATS integration, signed webhooks and SAML SSO, with API access coming soon. Which plan includes each is listed on the pricing page. Identity and right-to-work data sync to your ATS only after a consented reveal.

Why the platform works this way

The reasoning behind verified skills, blind evaluation and assessment integrity.

Hiring Playbook8 min read

What skills-based hiring actually is (and what it is not)

Skills-based hiring decides on demonstrated ability, not proxies like degrees or job titles. What it means in practice and where it fails.

Read
Fairness9 min read

Blind hiring: what the evidence supports, and what it does not

Blind hiring has one of the cleanest natural experiments in labour economics behind it, and real limits. What it fixes, and what it cannot.

Read
Integrity8 min read

Candidates are using AI in your assessments. Now what?

AI-text detectors are unreliable and disproportionately flag non-native speakers. What to do instead: assessment design, signals and human review.

Read
Hiring Playbook8 min read

Does your assessment predict anything? Validity for non-specialists

An assessment that feels rigorous can predict nothing. What validity and reliability mean, how to check yours, and the four ways hiring tests quietly break.

Read
Compliance9 min read

The EU AI Act and hiring: what recruitment teams are responsible for

AI used to recruit or evaluate candidates is high-risk under the EU AI Act. What that means for employers, what providers owe you, and what to ask vendors.

Read
Compliance8 min read

What "meaningful human oversight" actually requires

A reviewer who rubber-stamps 200 rankings is not oversight. What regulators mean by meaningful human involvement, and how to build a process that holds up.

Read

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