About

The measurement infrastructure for human capability.

In the AI era, workforce decisions — hiring, reskilling, restructuring — are only as good as the underlying measurement. Today, that measurement doesn’t exist. We don’t track learning. We measure capability. And once capability is measurable, workforce decisions become actionable.

Our mission

Replace checkbox compliance with real measurement.

Every organization trains people. None of them can prove it worked. $350 billion a year is spent on corporate training globally. Completion rates do not equal competency. Quiz scores do not equal mastery.

When auditors ask “can your nurses perform this procedure?” the answer is a checkbox, not measurement. When a CISO asks “how resilient is our workforce to phishing?” the answer is a simulation completion rate, not a statistically rigorous competency estimate.

Quantum Learning Machines replaces that. We built the engine that answers “does this person actually know this?” with calibrated, defensible, per-dimension measurement — and we deliver it as infrastructure that any platform can embed.

Company

Quantum Learning Machines, Inc.

Patent Pending

Mission

Calibrated Capability Measurement

Quantify whether people actually know what organizations need them to know — with the rigor of standardized testing and the scale of infrastructure.

Contact

For partnerships, enterprise, press, or research inquiries:

hello@quantumlearningmachines.com

The engine

Built on science that compounds.

The measurement engine behind QLM draws on decades of research in adaptive testing, cognitive science, and statistical estimation. Every interaction makes the engine smarter. Every organization that uses it deepens the calibration for everyone.

Multi-dimensional
Measures what matters, not just a single score
Captures multiple competency dimensions simultaneously — so you see not just how someone performs, but specifically where their strengths and gaps are.
Adaptive
The right question, at the right time
Every question is selected to maximize what we learn. Reach diagnostic precision in minutes, not hours. Confidence intervals tighten with every response.
Diagnostic
Not just a score — a map
“You’ve mastered X but not Y” — actionable capability maps that tell you exactly what to work on. The difference between a number and a plan.
Fair
Bias is caught during measurement, not after
Items that behave unfairly across demographic groups are excluded in real-time. Fairness is enforced as a production constraint, not reviewed as a report.
Predictive
Competency trajectories, not snapshots
“At this rate, this person will reach competency by June.” Growth prediction with confidence bands, not guesses.
Self-improving
The engine gets smarter with every interaction
Every response feeds calibration. New content calibrates itself from usage. The measurement compounds — this is the moat.
Trustworthy
Gaming and misfit are detected automatically
Random responding, gaming, and misfit patterns are flagged in real-time. Only genuine engagement contributes to the profile.
Honest
Every claim names its confidence and its limits
Per-claim validation status. Confidence intervals on every prediction. We name what the data can say and what it cannot. No overreach.
170,000+
Calibrated items
100+ exams
Across 25 domains
200+ careers
Mapped to outcomes
Validation

Numbers we stand behind.

We validate on independent datasets, publish what we find, and name the limits alongside the results. Trust is earned through transparency, not marketing.

Independent validation
✓
Every claim is validated against held-out data — never the training set. We publish what we find.
Published methodology
✓
Our measurement methodology, fairness approach, and validation results are available on our research page.
Confidence discipline
✓
Every prediction names its confidence interval. Every outcome names what it cannot tell you. No overreach.
Continuous calibration
✓
The engine recalibrates with every interaction. Measurement accuracy compounds over time — it does not degrade.

We validate on independent datasets, not the training set. We publish the numbers that do not favor us alongside the ones that do. Validation is not a marketing exercise — it is the mechanism by which the engine earns the right to be called measurement.

Honest discipline

We name what the data can and cannot say.

“Consistent with” — not “caused by.” Every claim carries its validation status. 18 bounding rules govern what the engine is allowed to assert.

Per-claim validation status
Every outcome the engine produces carries an explicit validation tag: validated, provisionally validated, or under study. No unmarked claims. No implied precision the data does not support.
18 bounding rules
Hard constraints on what the engine can assert. If the evidence is insufficient for a claim, the engine says so — it does not fill the gap with confidence it has not earned.
Confidence intervals, not point estimates
Every measurement comes with uncertainty. We surface the confidence band, not just the estimate. If the band is too wide to be actionable, we say that explicitly.
Compounding calibration
Every interaction — human and agent — feeds back into item calibration, ability estimation, and fairness monitoring. The engine does not just measure. It gets measurably better at measuring.
Three surfaces

One engine. Three ways to use it.

Individuals use it for free. Organizations buy measurement as a service. Platforms embed the engine directly.

For individuals

Measure your capability.

Free diagnostics across 100+ exams. Build a cognitive profile across 7 dimensions. Explore career fit, major fit, and career ladders. Upgrade to QLM Pro for AI-powered counselor, LinkedIn intelligence, and personalized roadmap.
  • 100+ exam diagnostics — free
  • 7-dimension cognitive profile — free
  • Career match, ladder, major fit — free
  • AI Counselor & LinkedIn Intelligence — Pro
  • Personalized roadmap & study plans — Pro
  • QLM Score: verified, portable credential — $99
Free explorer · QLM Pro $29/mo · Score $99
For organizations

Continuous competency measurement.

Statistically rigorous workforce competency monitoring. Skills-based hiring with calibrated fit scores. Strategic workforce planning with growth trajectory modeling. Audit-ready evidence that training actually works.
  • Competency monitoring at $2-5/person/mo
  • Skills-based hiring + role fit scoring
  • Growth trajectory prediction
  • Regulatory compliance evidence
  • Cross-domain skill transfer analytics
  • Workforce risk quantification
Platform $5K/mo · Enterprise $20K+/mo
For platforms (OEM)

Embed the engine.

Drop real competency measurement into any LMS, HRIS, or security awareness platform. Multi-tenant API, JS embed widget, webhook events, auto-generated SDKs. Your customers get measurement. You get a premium add-on. We get scale.
  • <qlm-assessment> embed widget
  • Multi-tenant API with scoped keys
  • Webhook events for every state change
  • Python + Node.js SDKs
  • Sandbox for partner engineering
  • Partner revenue dashboard
70/30 revenue share · $2K/mo minimum
Careers

We’re hiring.

We’re looking for engineers, researchers, and product builders who want to build something that matters. If you care about measurement, precision, and building infrastructure that gets better every day — we want to talk.

Reach out