Legacy measurement is slow, narrow, and hard to update.
The engine underneath hasn’t kept up. QLM replaces the adaptive scoring and evidence layer.
Your platform delivers tests. QLM makes them measure real capability.
Legacy measurement is slow, narrow, and hard to update.
The engine underneath hasn’t kept up. QLM replaces the adaptive scoring and evidence layer.
Items recalibrated annually. New content waits months to go live. Your content team moves fast — your engine makes them wait.
One score per test. No sub-skill diagnostics. No actionable feedback. Your customers get a number when they need a map.
DIF analysis after the fact. Biased items serve thousands of test-takers before anyone reviews the report. That’s not fairness — that’s damage control.
Drop-in adaptive scoring, calibration, and evidence infrastructure. Your content. Your brand. Our engine.
Choose the depth of integration that matches your roadmap. Every option preserves your brand, your content relationship, and your customer experience.
The same test-taker, the same content domain. The only difference is the engine underneath.
| Before (Legacy) | After (QLM Engine) |
|---|---|
| 40–60 items to converge | 15–25 items (faster convergence) |
| One score | 7-dimension diagnostic map |
| “You scored 72%” | “Strong in analysis, gap in inference” |
| Fixed test length | Adaptive — stops when confident |
| Annual recalibration | Continuous from every response |
| DIF review quarterly | Real-time fairness enforcement |
| No growth tracking | Predictive competency trajectory |
| Manual content QA | Automatic quality gates + rotation |
Production-grade API with everything you need to integrate in under two weeks. No vendor lock-in on your data.
// Start a measurement session const session = await qlm.sessions.create({ bank_id: "your-custom-bank", dimensions: ["D1", "D2", "D3", "D4", "D5"], max_items: 25, confidence_target: 0.05, }); // Get the next optimal item const item = await qlm.sessions.nextItem(session.id); // Submit response — engine updates all dimensions const update = await qlm.sessions.respond(session.id, { item_id: item.id, answer: "B", time_ms: 12400, }); // update.dimensions → { D1: 0.82, D2: 0.71, ... } // update.converged → true when all dimensions meet target SE
If your platform delivers assessments, certifications, or competency credentials — and you need measurement infrastructure that matches the rigor of what you certify — this is for you.
Book a 30-minute technical demo. We’ll show the engine measuring competency in your domain — doing something your current engine can’t.
Book Technical Demo