Assessment Infrastructure

Replace your measurement engine. Keep your brand.

Your assessment platform delivers tests. Our engine makes them measure. Multi-dimensional adaptive estimation that converges faster than legacy adaptive testing — embedded as infrastructure you control.

See the Engine Book Technical Demo

Faster

Adaptive convergence

7 dimensions

Simultaneous estimation

25 domains

Pre-calibrated banks

< 2 weeks

Integration time

The problem with legacy engines

Your engine was built for a different era.

Assessment companies built their measurement engines 10–20 years ago. Single-dimension. Fixed-length. Manual calibration cycles that take months. Fairness reviewed quarterly, not enforced in real-time.

Every competitor has the same limitations. Your differentiation is brand and content, not technology. And your customers are starting to notice.

The engine underneath hasn’t kept up. New items wait months to go live. Your tests measure one thing when they could measure seven. Your fairness process catches biased items after thousands of people have already seen them.

Manual calibration

Items recalibrated annually. New content waits months to go live. Your content team moves fast — your engine makes them wait.

Single dimension

One score per test. No sub-skill diagnostics. No actionable feedback. Your customers get a number when they need a map.

Static fairness

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.

The engine

Eight capabilities your current engine doesn’t have.

Drop-in measurement infrastructure that replaces the adaptive selection, scoring, and calibration layer of your platform. Your content, your brand, our engine.

Multi-dimensional

Measures multiple competency dimensions simultaneously

Not just one score. Seven distinct dimensions estimated in parallel — so the output is a diagnostic map, not a number.

Adaptive convergence

Reaches diagnostic precision in 15–25 items

Faster adaptive convergence than traditional testing. Every item is selected to maximize information gain across all dimensions simultaneously.

Real-time calibration

New items calibrate from live usage — no manual cycles

Every response refines the calibration of every item. New content goes live in hours, not months. No annual recalibration process.

Continuous fairness

Biased items excluded during measurement, not after review

Fairness is enforced as a production constraint on every single item selection. No test-taker ever sees a flagged item.

Growth prediction

“At this rate, this person reaches competency by [date]”

Competency trajectories with confidence bands. Not snapshots — projections. Your customers get a timeline, not just a status.

Content quality gates

Poorly discriminating items flagged and rotated out automatically

Automatic quality screening. Items that don’t discriminate well are sidelined. Your bank stays sharp without manual review cycles.

Person-fit detection

Gaming, random responding, and misfit flagged in real-time

Response patterns that don’t fit the measurement model are detected during the session. Only genuine engagement contributes to results.

Self-improving

Every interaction compounds calibration accuracy

The engine gets measurably better with every response it processes. Your measurement precision improves automatically over time — not just when you run a recalibration.

170,000+

Calibrated items

100+ exams

Across 25 domains

< 0.05 SE

Typical measurement precision

How it works

Three ways to integrate.

Choose the depth of integration that matches your roadmap. Every option preserves your brand, your content relationship, and your customer experience.

Option A

Engine Replacement

Replace your adaptive selection and scoring engine. Keep your content, your brand, your platform. Our engine sits behind your API.

Your items, our calibration
Your UI, our adaptive selection
Your scoring rubric, our multidimensional estimation
Your reports, our confidence intervals

Custom · Minimum $50K/yr

Option B

Engine + Banks

Replace your engine AND get access to 25 pre-calibrated domain banks with 170,000+ items. Launch new assessment products in days, not months.

Everything in Engine Replacement
25 domain banks (500–3,000 items each)
Bank enrichment pipeline (9 steps)
Cross-domain skill transfer analytics

Custom · Minimum $100K/yr

Option C

White-Label Platform

Run the full QLM platform under your brand. Your domain, your design, your customers. We provide the measurement infrastructure.

Full measurement platform
White-label branding + custom domain
Dedicated infrastructure
SSO/SAML integration
Custom SLA

Custom · $200K+/yr

What changes for your customers

Before and after.

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

Integration

Built for engineering teams that ship fast.

Production-grade API with everything you need to integrate in under two weeks. No vendor lock-in on your data.

API

RESTful, versioned, rate-limited, idempotent

Auth

API keys with scoped permissions (read, write, admin)

SDKs

Python + Node.js — auto-generated from OpenAPI 3.1

Embed

<qlm-assessment> web component — drop into any page

Webhooks

9 event types, HMAC-signed payloads, retry with backoff

Data

Your infrastructure or ours — full data portability

Compliance

SOC 2 ready · HIPAA BAA available · GDPR-compliant data handling · Data residency options

// 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

Who this is for

Built for companies where measurement is the product.

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.

Assessment & Learning Platforms

You deliver tests or adaptive learning — and your item selection is still random or fixed-form

You have a question bank but no calibration pipeline — item difficulty is assigned by hand, not measured

You report pass/fail but can’t tell a customer which dimensions drove the result

You want to add adaptive measurement without building a psychometrics team

Testing & Proctoring Organizations

You administer high-stakes exams at scale and need shorter tests with equal or higher reliability

You collect response data but don’t have an IRT calibration pipeline extracting value from it

You want real-time scoring and dimensional reporting — not batch-processed results days later

You need to prove measurement fairness across demographics with statistical evidence, not assertions

Credentialing & Certification Bodies

You issue competency-based credentials and need measurement that holds up to regulatory audit

You require ongoing recertification but can’t justify giving the same 200-question exam every cycle

You want to detect credential decay over time — not just verify competency at one point

You need white-label infrastructure that carries your brand, not ours

Your content. Our engine. Their measurement.

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