Talent intelligence, visualized
An AI-native talent intelligence platform that reads every résumé, scores fit against the real role, and shows exactly why — with the evidence attached.
The problem, in proportion
It was never the volume. It's the pile.
Of every 100 résumés, only 30 get a real look. The other 70 aren't rejected — they run out of clock.
A skipped score or a promoted unknown leaves no record of why — until an auditor asks.
Keyword tools reward the paper-perfect résumé, then lose it by day 90 — untraceably.
How the score is built
Nine signals. One explainable number.
Intelletto.ai runs nine scoring buckets, re-weighted by seniority band from Junior to C-Suite, and tightened after every hired cohort on 30 / 90 / 180-day performance data. Three engines turn them into one answer:
Who is actually a fit.
Who actually performs.
Whether you can prove it.
And it all lives inside the ATS you already run. No rip-and-replace.
Note. Nine buckets shown at equal weight for clarity; in production the weights shift automatically by seniority band and re-tune on hired-cohort outcomes.
The payoff — this quarter
Five metrics. The change this quarter.
Source. Current-quarter measurements vs. the pre-implementation baseline. Each figure is the measured change on that metric.
The full toolkit
What it does. What you get.
Talent Intelligence
Every résumé structured and normalised to your taxonomy, web-corroborated — not keyword-matched.
Outcome Intelligence
Nine seniority-weighted buckets that re-tune after every cohort on 30/90/180-day data.
Governance Intelligence
Reason codes, source passages, and a 14-page audit report a regulator can verify independently.
Seniority-Aware Scoring
“Do the work?” for juniors becomes “own the function?” at C-level. Weights shift automatically.
ATS Sidecar Integration
API into SAP, Workday, Oracle, Greenhouse, Lever, BambooHR, Salesforce. No replatform.
Shadow → Gated → Automate
It scores silently, a human gates, then you automate only the reqs you choose. Reversible.
Why it's different
The things others can't show.
It shows its working
Every score traces to the source PDF bytes via SHA256. Candidates, hiring managers, and regulators all get the same answer to “why?”
It teaches itself
Intelletto.ai checks its scores against how hires actually perform, so the rubric sharpens after every cohort — measurably smarter each quarter.1
It polices bias
A separate model audits every job ad, outreach note, and rationale for gendered language, age, and origin bias — flagged before it reaches a candidate.
1. Trend shown is schematic — accuracy rises and stabilises as cohort-outcome data accumulates. | NYC Local Law 144 (2021) requires an independent annual bias audit of any automated employment decision tool; Intelletto.ai’s continuous record is built to pass it, not replace it.