GLS AI Accreditation Engine

Understand. Assess. Improve. Accredit.

The GLS AI engine reads your learning content and supporting evidence, then assesses it against the structured criteria of a published GLS accreditation standard — criterion by criterion, with the evidence source recorded.

Submit a course

What the engine does

Structured criteria, not a compliance opinion

GLS does not ask a language model whether a course “looks compliant.” Every assessment runs against the GLS criteria database: clause, requirement, required evidence, assessment type, scoring rules and weight. The AI must attribute each finding to evidence you supplied, and it must never invent evidence.

Understands course structure and sequencing
Extracts learning objectives and outcomes
Analyses learning content and resources
Analyses assessment and competence measurement
Analyses accessibility and learner support
Analyses evaluation and feedback mechanisms
Maps identified evidence against GLS criteria
Identifies missing evidence and potential gaps
Generates recommendations with an evidence source
Compares course versions for reassessment impact

Illustrative assessment record

Criterion 4.2 — Learning Outcomes

Partially aligned

Evidence found: Module 1 — page 6
AI analysis · AI-generated: “The course contains defined learning outcomes; however, some outcomes are not measurable and are not consistently linked to assessment activities.”; Confidence 91%
Recommended action: “Revise learning outcomes 2 and 4 to include measurable learner performance.”
Reviewer decision: Held for GLS reviewer assessment. AI findings are advisory and can be overridden by the reviewer.

Illustrative example. Not a real accreditation record.

AI assists. People accredit.

The GLS AI engine never issues accreditation. It prepares an auditable, evidence-mapped assessment for a GLS reviewer, who accepts, rejects, overrides or requests further evidence before any accreditation decision is made.

See the full process