What problem does it solve?
Generic AI-generated safety training paperwork is often vague, lacks named role-specific evidence, uses weak administrative controls as the sole hazard fix, and leaks personal or appraisal data — leading to regulator rejections, ineffective training programmes, and compliance breaches.
Core Features & Use Cases
- Role-by-competence gap matrix: Builds a scored matrix mapping each named role to required competencies, banded against the shared 4-level competence scale from named evidence sources, flags single-points-of-failure (SPOFs) by role (not identity), and tracks certification expiry and refresher dates.
- Regulatory compliance grounding: Built on ISO 45001 clause 7.2 (competence) and 7.3 (awareness), with jurisdiction-specific legal-required competencies cited (UK MHSWR 1999 reg. 13, US OSHA standards, India Factories Act 1948, etc.) that are never omitted or downgraded to "pass".
- Prioritised, costed training plan: Emits SMART, owned, dated training actions prioritised by gap size, task risk, and legal mandate, with training framed as an administrative control paired with higher-order hazard controls (elimination, substitution, engineering) per the hierarchy of controls.
- Use case: For a UK construction scaffolding crew subject to an audit finding, the skill produces a compliant TNA that flags the statutory competent-person scaffold inspection requirement, identifies the sole night-shift inspection-competent worker as a SPOF, and outputs a costed plan with named owners and ISO due dates.
Quick Start
Ask the skill to build a training needs analysis for your named site roles, specifying your jurisdiction, available competence sources, and the driver for the TNA (e.g. audit finding, post-incident, refresher cycle).
