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Hiring platform · for the AI era

The AI-native hiring platform for technical teams.

Chiron runs your technical hiring end to end — jobs, pipeline, scheduling, analytics — around an assessment that measures real engineering work with an AI pair. Every stage moves on evidence you can defend.

// the pre-AI screen

Tests recall under surveillance.

Résumés written by AI
Take-homes completed by AI
Leetcode: seen the question?
The wrong question, gameably asked
// the Chiron session

Measures the real modern job.

Real work, with an AI pair
Planted errors — disclosed, not located
A curveball, mid-flight
Three signals + a divergence check
The idea at the core
Generative AI destroyed the signal value of every cheap hiring artifact. Chiron turns the AI from the cheating vector into the measurement instrument.

A leetcode question tells you whether a candidate has seen a leetcode question. The work doesn't look like that anymore — so the screen shouldn't either. Chiron screens for how someone thinks, decides, and pushes back when the AI is wrong.

The workspace

A real editor, a real spec, a real pair. No fishbowl.

Chiron candidate — working session in a real editor
What we measure

Three independent signals. One natural session.

01Execution
The code
Did the work work? We score concurrency, retry behavior, edge-case handling, cancellation — the things that get bug reports filed in production.
4 dimensions · 1–5 anchored
02Engineering judgment
The reasoning
Why these choices? Lyra asks the candidate to walk through trade-offs at checkpoints. We score the alternatives they articulated — and the ones they didn't.
3 dimensions · defense + transcript
03AI collaboration
The AI direction
Lyra produces some code that is deliberately, subtly wrong. We watch what the candidate does with it — accept, reject, edit, ignore. Disclosed up front; never gamified.
3 dimensions · review + reasoning
The integrity check is structural, not surveillance. When execution is strong but the explanation behind it is thin, the divergence shows — a built-in tell, no webcam required.
How divergence works
What your team reads

Evidence, not a verdict.

Every score expands to the quote, the diff, or the moment that produced it. The reviewer reads, considers, and decides. Chiron recommends; the human calls.

Engineering
judgment
Reasoned trade-offs clearly; chose injectable back-off.4/ 5
Transcript · defense topic 2
"Injectable because the right back-off is endpoint-dependent — jittered exponential for the public API, fixed for internal."
Chiron console — candidate result detail
How it feels for the candidate

A pair, not a proctor.

Lyra reads as a calm, helpful colleague — a senior teammate the candidate has never met. Lyra drafts, reviews, and asks questions to understand their thinking. Disclosed up front: Lyra is also fallible, and reviewing that work is part of the job.

Quiet by default
No timer alarm, no jump-scare modals, no streaks. Calm even when time runs short.
Disclosed, not hidden
The candidate is told the AI is fallible and that reviewing Lyra's code is scored.
Saves and pauses
Disconnect or refresh — work is safe; the clock pauses.
Lyra · your AI pairtyping
Lyra
Glad to pair on this. Happy to draft, review, or rubber-duck — what's your first move?
ATYou
Queue interface first. I want a test for the concurrency cap before I touch retries.
Lyra
Good call. Quick check before retries — what should the queue do when a request times out mid-flight?
The curveball

The spec changes mid-flight. Like it does at work.

Once per session the requirements shift — calmly. Lyra flags it, the brief updates with what changed, the candidate acknowledges and adapts. We score how they handle the pivot, not whether they flinch.

Task briefbrief updated
Build a bounded work queue with a concurrency cap
Add retry with backoff for failed jobs
Process requests strictly in arrival order
+Cancel in-flight work when a request times out mid-flight
The whole platform

The assessment is the heart. The pipeline moves on its evidence.

ATS & pipeline
A visual pipeline board and review queue. Every stage carries the assessment evidence forward.
Scheduling
Candidate self-scheduling against panel calendars, with idempotent reminders and calendar sync.
Analytics
Funnels, time-in-stage, reviewer calibration, offer outcomes, accept-by-band — export-ready.
CRM & sourcing
A prospect CRM, bulk import, source attribution, and a Rediscover surface for past applicants.
Careers site
A public job board, apply flow, offer acceptance, and self-schedule — SEO-ready and server-rendered.
Platform & admin
SSO, TOTP two-factor, org/teams, billing, audit log, data residency, and container hosting at scale.
Chiron console — pipeline board
Built for fairness

Fairness isn't a polish pass.

Chiron is designed against NYC Local Law 144 and the EU AI Act from the foundations up — not retrofitted. Every dimension is auditable. Every recommendation is reviewed by a human.

WCAG 2.1 AA
Accessible by construction
Contrast, keyboard, reduced-motion, never color as the only signal — across both surfaces.
NYC LL 144
Built to be bias-audited
Designed against NYC LL 144's four-fifths rule so disparate impact can be independently audited.
EU AI Act
High-risk by design
Hiring is high-risk under the Act. Article 14 oversight by construction — the reviewer always decides.
Evidence
No score stands alone
Every dimension expands to a quote, diff, or moment. Reviewers always have grounds.
Private beta · founding teams

Get a first round that's worth the engineer's time.

We're onboarding a small group of founding teams. Join the waitlist and we'll open a seat — and calibrate your first assessment with you.

Private beta · no card · we email you when a seat opens.