Assessment platforms, LMS providers, ATS vendors, and HRIS systems all face the same problem: their users need calibrated measurement, but building rigorous psychometrics in-house takes years and costs millions. QLM provides the measurement infrastructure as a drop-in layer — your end users see your brand and stay inside your product; the item calibration, adaptive engine, fairness audit, and Profile portability are QLM's. Four SDKs, three integration patterns, SOC 2 compliant, 70/30 revenue share. The trust boundary is architecturally enforced — partners cannot manipulate calibration, and the methodology disclosures exist in every deployment regardless of branding tier.
Pick the integration pattern that fits your platform architecture and brand requirements. Each pattern preserves calibration integrity, fairness audit on every event, and cross-partner Profile portability. The trust boundary is non-negotiable across all patterns — the methodology accessibility, Profile verification, fairness audit transparency, and limits surfacing exist regardless of branding tier.
QLM SDK renders the full measurement experience inside your platform container. Lowest integration burden — your team ships in weeks, not months.
REST API drives measurement. You control the entire platform UI; QLM runs the engine and calibration in the backend.
SDK for question presentation, API for results processing. Pick what to customize, what to inherit from QLM defaults.
Same items, item-pool selection, and calibration models as first-party. Partners cannot edit items, reorder them, or insert custom items.
Real-time fairness monitoring runs on every measurement regardless of platform origin. Items pulled from the global bank benefit all partner deployments.
Users own their Profile. A user generating a Profile through your platform can take it elsewhere with appropriate consent — the portability commitment is universal.
Profile artifacts signed by QLM keys. Third parties verify against QLM's public API regardless of which platform mediated the measurement.
Platform companies embed QLM measurement to solve fundamentally different problems — but they all share the same root need: calibrated, defensible, bias-audited measurement that would take years to build internally. QLM works across the full stack of talent and learning platforms. The same SDK, the same trust guarantees, the same revenue share model — configured for each platform context.
Embed pre-course and post-course diagnostics to measure actual capability gain rather than content consumption. Most LMS platforms track completion; QLM measures whether learners actually acquired the skill. Adaptive item selection calibrates to each learner's level, producing a defensible baseline and a post-course delta that justifies the learning investment — to learners, to managers, and to procurement.
Replace resume screening with calibrated role-fit measurement at the top of the funnel. ATS platforms already own the candidate workflow — adding QLM measurement turns a document-sorting system into a genuine evaluation engine. Structured, bias-audited measurement produces defensible evidence for every hiring decision, with Profile artifacts that candidates can take with them regardless of hiring outcome.
Continuous competency monitoring and skills gap analysis embedded in the systems HR teams already live in. HRIS platforms own the employee record; QLM adds a calibrated measurement layer that turns self-reported skills into verified capability profiles. Periodic re-measurement tracks genuine development over time, producing the skills graph that L&D, succession planning, and workforce analytics all need but rarely have.
Add adaptive measurement to existing content libraries and replace legacy item banks with QLM's calibrated, fairness-audited engine. Publishers already own extensive content — QLM adds the adaptive diagnostic layer that turns static assessments into calibrated measurement. Item banks updated continuously, fairness monitoring built in, SOC 2 compliant data handling throughout. No need to rebuild the psychometric infrastructure that takes decades to validate.
When measurement runs inside a partner platform, several trust questions arise. Each has an architectural answer rather than a contractual one. Partners cannot manipulate calibration even if they wanted to — the engine runs server-side, items are immutable to partners, and signature integrity is preserved across every deployment.
Every measurement event and Profile signed by QLM keys. Partners cannot sign artifacts as if they were QLM-issued. Signature includes partner_id but signing authority is QLM's — the platform brand and the measurement authority are clearly separated.
Platform sends QLM: end_user_id, demographic data (with consent), session config. QLM sends platform: session_id, items, result, signed Profile artifact. Platform does not receive raw response data — the measurement stays in QLM's custody throughout.
Fairness issues detected in any platform's user population produce item pulls affecting all partners. Calibration improvements happen across the entire system — the item bank is shared infrastructure that makes every deployment more robust over time.
QLM's platform partnership terms include hard architectural constraints. These exist because the measurement's integrity — and the trust of every end user on every platform — depends on them being non-negotiable. Five things platform partners explicitly cannot do, even in full white-label tier.
Most platform partners use 70/30 revenue share on measurement-derived revenue. Platforms with pricing models that don't cleanly attribute revenue to individual measurement events use usage-based pricing instead. Strategic full white-label partnerships are bespoke and case-by-case.
On measurement-derived revenue. One-time implementation fees $50-250K depending on integration complexity. Configurations 1-3 (full co-brand to methodology-attributed white-label) available. Best fit for LMS and ATS platforms where measurement is a billable line item.
For platforms where revenue share attribution is structurally difficult. $0.40 per shorter event (5-15 min), $1.50 per baseline (15-25 min), $4.00 per intensive (30-90 min). Volume discounts at 10K, 100K, 1M events/year. Default for HRIS and edtech publisher deployments.
Bespoke partnerships for top 5-10 strategic platform partners. Different revenue share, longer terms, contractual exclusivity in the partner's market segment. Methodology accessibility and Profile portability non-negotiable regardless of white-label depth.
Currently accepting platform partnerships across LMS, ATS, HRIS, and edtech publisher categories. Implementation is 8-16 weeks; the trust boundary is non-negotiable.