AI-powered applicant tracking

Hire with clarity.Not complexity.

A modern ATS for teams that want structured hiring, AI assisted screening, and one place to run the full process from apply to offer.

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Dashboard

VK

Avg. candidate score

78%

Up 4% from last month

Open roles

12

+2 this week

In pipeline

847

+48 this week

Interviews

23

5 today

Pipeline trend

Applied Hired
MarAprMayJunJulAug

The problem

Resumes describe work.
They never prove it.

Hiring teams drown in identical PDFs while the actual signal shipped repositories, real portfolios, how someone reasons under pressure sits untouched. AI.Prof turns that signal into a structured, comparable score before a human spends a single minute.

Every one of these failures has the same root cause: the evidence exists, but nothing reads it.

  1. A towering stack of near-identical résumé pages on a pale desk

    Screening bottleneck

    Hundreds of applications per role, reviewed in seconds each, with no consistency between reviewers.

    6saverage time spent per résumé
  2. A brass balance scale tipped unevenly, one pan empty

    Unstructured judgement

    Weights and thresholds live in people's heads, so two hiring managers rank the same pipeline differently.

    2×divergence between reviewers on one pipeline
  3. A closed laptop set aside beneath a printed page

    Best proof, Ignored

    GitHub, portfolios and coding profiles are skimmed at best the strongest proof of ability goes unread.

    0repositories actually opened in most screens
  4. An empty open filing folder with nothing inside

    No record to fall back on

    When a decision is challenged, there is no record of what was measured or why it mattered.

    —auditable record left behind after a rejection
THE SOLUTION

One platform.
Every hire.

AI.Prof replaces your stack of disconnected tools with a single AI assisted ATS built specifically for teams that value speed, signal, and structured hiring.

AI Resume Scoring
Profile Analysis
AI Interview Engine
Coding Assessments
Real time Analytics
Live Projects
Start Hiring Now
AI.Prof

Upcoming Candidates

3 Evaluated
Marcus Reed
Marcus Reed

Senior Full Stack Eng.

94%
Tech Round Pass10m ago
Elena Rostova
Elena Rostova

AI / ML Architect

91%
Repo Evaluated1h ago
David Nguyen
David Nguyen

Lead Product Designer

88%
AI Interview Done3h ago

Auto Ranked

Zero manual screening needed

100% Signal
Our Mission

We think hiring should feel less like guesswork.

We started AI.Prof because hiring teams were stuck choosing between drowning in manual work or trusting an AI black box nobody could explain. So we built something in between AI that surfaces the evidence, companies set what matters, and the final call always stays with a person. No rigid pipeline, no scores nobody can explain just a process that helps people hire well.

Team collaboration

The Hiring Pipeline

Skip it. Reorder it. Own it.

Every stage below is optional and drag reorderable per role. Build a hiring flow that reflects how your team actually evaluates talent.

Pipeline configuration
01ApplyRequired
02AI Analysis
03Interview
04Coding
05Live Project
06Decision & OfferRequired
Coding hiring pipeline stage

Active stage

Coding

04 / 06

Unaided or AI assisted coding rounds with the Veda assistant.

Why teams switch

Built for teams who look past the resume.

AI.Prof replaces gut feel screening with configurable, auditable evaluation without losing the human at the end of the pipeline.

AI scoring engine

Every candidate gets a normalized, explainable score.

Weights and thresholds are set per role. AI.Prof scores resume match, GitHub depth, portfolio craft, and interview performance then ranks candidates on a single comparable scale.

Resume

92

GitHub

78

Portfolio

85

Interview

88

Per role config

You set the rules.

Weights, thresholds, stage order, and which modules run all decided by the hiring manager. No two roles have to look alike.

Role Config
Real code, not stars

We read the actual code.

Commit cadence, complexity, contribution depth. AI.Prof evaluates engineering substance not vanity metrics.

AvatarAvatarAvatar
3 active repos
412 commits · 18 PRs
Latest commit · 2h ago+128 −34
TypeScript · 64%Python · 36%
Candidate safe

Scoring stays internal.

Candidates see a clean progress dashboard never raw scores or rankings. Share high level feedback only when you choose to.

Candidate View
PROTECTED
Stage 03 / Tech RoundIn Review
Raw evaluation matrix hidden
Governance

Auditable by design.

Cross-tenant audit logs, RBAC roles, and a global kill switch. Every action by tenants and platform admins is logged.

Audit TrailENCRYPTED
✓ RBAC Access14:32:01 UTC
⚡ Tenant Isolated14:31:45 UTC
🛡 Kill Switch Armed14:28:10 UTC
For candidates

A hiring experience candidates actually respect.

AI.Prof is built for employers, but it respects the people on the other side. Candidates get transparency, a fair process, and a real interview not a keyword filtering black box.

Candidate in a job interview

Candidate Progress Tracker

LIVE STATUS
Application submitted
PASSED
AI analysis complete
PASSED
Interview scheduled
PASSED
Final decision pending
01Visibility

A progress dashboard, not a black hole

Candidates track their status in real time application received, under analysis, interview scheduled, decision instead of wondering if anyone ever opened their resume.

02Fairness

One submission, evaluated fairly

A single unified application resume, GitHub, portfolio links submitted once. Every candidate is analyzed on the same evidence, the same way.

03Interview

Interviews that meet them where they are

One continuous interview that blends chat, voice, and video. The AI picks the right mode for each question instead of scheduling three separate rounds.

04Feedback

Optional feedback, when the company allows it

When a company enables evidence sharing, candidates can get high level, evidence based feedback on their projects and interview instead of silence.

Comparison

Traditional way vs AI powered automation

Traditional way
AI.Prof automation
VS
  • Resume keyword screening
  • Subjective, inconsistent scoring
  • One size fits all evaluation
  • Black box AI screening tools
  • Claims taken at face value
  • Shallow one off interviews
  • No visibility into real code
  • Same process for every role
  • Reviewer hours per candidate
  • Gut feel final decisions
  • Evidence from resume, GitHub, projects
  • Consistent, evidence backed scoring
  • Company configured per role weighting
  • Transparent, traceable scoring
  • Verified against real shipped work
  • Unified multi modal AI interview
  • Deep code & architecture analysis
  • Modular features per role's needs
  • Minutes to triage a ranked shortlist
  • Human decision, AI backed evidence

Packages

Buy a bundle, or just the modules you use.

Every analysis module is also available individually from the feature marketplace, so you never pay for a pipeline stage you switched off.

Starter

For teams running their first structured, evidence based roles.

$390/ month

  • Branded careers page
  • Resume × JD scoring
  • Chat interviews
  • Up to 5 active roles
  • Admin + Recruiter roles
  • Live project assessment
  • SSO
Start with Starter

Growth

Most chosen

For scaling teams that hire engineers and designers continuously.

$1,180/ month

  • Everything in Starter
  • GitHub + portfolio analyzers
  • Voice and video interviews
  • Unaided & AI assisted coding rounds
  • Full RBAC and analytics
  • Unlimited active roles
  • Data residency pinning
Start with Growth

Enterprise

For multi brand organisations with compliance obligations.

Custom

  • Everything in Growth
  • Live project assessment
  • SSO, SCIM and custom RBAC
  • Data residency and retention controls
  • Model version pinning
  • Dedicated support with audited access
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FAQs

Common Questions

Everything you need to know before booking a demo.

Ready when you are

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