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— AI Agent · Hiring

Screen every resume — fairly, in seconds.

An AI recruitment platform that parses resumes, scores candidates against the role on multiple dimensions, and ranks them with explainable, bias-aware logic — so your team spends time on people, not stacks of PDFs. Wired into your ATS.

Book a live demo → See the architecture
80%less screening time · explainable & bias-aware · live in 3–4 weeks
80%Less time screening
Bias-awareMasked & audited
100%Explainable scores
3–4 wksTo production
— What it does

The top of your funnel, handled.

Not a keyword filter that rejects good people. A scoring engine that reads resumes like a thoughtful recruiter — and shows its reasoning.

— 01

Resume parsing

Reads any format — PDF, DOCX, LinkedIn — into structured profiles: skills, experience, education, gaps.

  • Any format in
  • Structured profiles
  • Skills & timeline extraction
— 02

Multi-dimensional scoring

Scores each candidate against the role on skills, experience, seniority and role fit — not just keywords.

  • Skills · experience · fit
  • Role-specific rubrics
  • Weighted scoring
— 03

Bias-aware ranking

Masks name, gender and other signals during scoring and audits outcomes for adverse impact.

  • Name / gender masking
  • Adverse-impact checks
  • Configurable fairness
— 04

Explainable shortlists

Every score comes with reasons and evidence from the resume — defensible to hiring managers and auditors.

  • Reasons on every score
  • Evidence highlights
  • Manager-ready summaries
— 05

Screening questions

Generates and scores role-specific screening questions and take-homes to go beyond the resume.

  • Auto-generated questions
  • Answer scoring
  • Take-home evaluation
— 06

ATS-native

Ranks inside the ATS you already use, syncing scores, notes and status automatically.

  • Greenhouse · Lever · Workday
  • Auto-sync scores & notes
  • No new tool to adopt
— How it works

The architecture, end to end.

Candidates flow in from your ATS and job boards, resumes are parsed and enriched, the scoring engine ranks them bias-aware and explainable, recruiters review, and results sync back to the ATS.

Runs in your cloud or a private VPC · EEOC & GDPR-aware · candidate data never trains third-party models

— Connects to

Plugs into the stack you already run.

Works inside the ATS your team already lives in, and the boards you source from.

Greenhouse
Lever
Workday
Ashby
BambooHR
LinkedIn
Indeed
Gmail
Slack
GPT-4o
Claude
Postgres
Your VPC
— Deployment

From role rubric to shortlists in weeks.

A fixed-scope rollout — we calibrate scoring on your real roles and past hires before it ranks a single live candidate.

01

Discovery — Week 0

We map your roles, hiring criteria, ATS and fairness requirements, and agree quality-of-hire targets.

02

Calibrate — Weeks 1–2

We build role rubrics, connect your ATS, and calibrate scoring against past successful hires.

03

Validate — Weeks 2–3

We test rankings and run adverse-impact checks with your talent and legal teams before go-live.

04

Go live & monitor — Week 4+

Rollout with funnel and fairness dashboards. Optional retainer for new roles and rubric tuning.

— Enterprise-grade

Faster hiring you can stand behind.

AI in hiring is under a microscope — legally and ethically. This is built to be fair and explainable, not a black box.

— 01 · Explainable & auditable

No black-box rejections.

Every score comes with reasons and evidence from the resume, and outcomes are audited for adverse impact — so hiring managers trust the shortlist and your legal team can defend the process.

— 02 · Bias-aware by design

Fairness isn't an afterthought.

Names, gender and other signals are masked during scoring, fairness thresholds are configurable, and adverse-impact monitoring is built in — because faster screening should never mean less fair screening.

— Frequently asked

The questions talent leaders ask first.

Something missing? Email Prakash directly — same-day replies, no SDR layer.

Isn't AI screening biased?
It can be if done carelessly — which is why this platform masks name, gender and other signals during scoring, audits outcomes for adverse impact, and exposes fairness thresholds you control. It's designed to reduce bias, not encode it, and every decision is explainable.
Will it reject good candidates like a keyword filter?
No. It scores on skills, experience, seniority and role fit with evidence from the resume — not keyword matching — so strong candidates with non-standard resumes still surface, each with a reason for their score.
Can we defend the decisions?
Yes. Every score includes reasons and highlighted evidence, and the platform is EEOC and GDPR-aware with adverse-impact monitoring — so both hiring managers and auditors can see exactly why a candidate ranked where they did.
Does it work with our ATS?
Yes — it ranks inside Greenhouse, Lever, Workday, Ashby and others, syncing scores, notes and status automatically. There's no separate tool for recruiters to adopt.
Is candidate data secure?
Yes. We deploy in your cloud or a private VPC, and candidate data never trains third-party models. We support GDPR and are EEOC-aware in how scoring and auditing work.
How long to deploy and how is it priced?
Live in 3–4 weeks after calibrating on your roles and past hires. Pricing is a fixed setup fee plus a monthly platform fee by hiring volume.
— See it screen a real req

Book a demo. Bring an open role and a resume stack.

A 30-minute session with Prakash or a senior AI engineer — never an SDR. Bring a live requisition and we'll show the platform scoring and ranking real candidates, with reasons.

Book a live demo →
— Founder will reply personallyPrakash Singh · Matrytech