Self-reported confidence is not a hiring signal. Without a skills baseline, development budgets chase whoever asked loudest.
When AI readiness is self-reported, hiring screens for confidence and L&D buys courses for the loudest request. Peer reviews, titles and tool licenses disagree. Scale that without a baseline and you fund the wrong people — then face a works council asking what you measure before anything that looks like surveillance ships.
One skills model, assessments to check it, recruiting keyed to demonstrated skill, and development plans that close measured gaps — with a public data boundary for what AI features never touch.
The same platform modules as on the landing — only the ones that act on the risk above.
Build living competency frameworks and see what your workforce can actually do.
Self, 180° and 360° assessments with calibration and detailed reporting.
Knowledge tests with generated questions and automatic scoring.
Hire for demonstrated skills — resume scoring, skill checks, interview analysis.
Personal development plans that close measured skill gaps.
Grades, org structure and career ladders connected to skills.
Internal vacancies and projects matched by competency profiles.
A sandbox preloaded with a sample team and its usage signals — no installs, nothing to connect. Your own data comes later, on your terms.
