SkillsDBvs365Talents

365Talents has built a credible skills intelligence platform around one hard problem: getting a first skills map across a large workforce without asking thousands of people to fill in forms. Its AI detects skills from HR data, job descriptions, and internal content, then keeps that inventory moving as people take on new projects. For a European enterprise with many entities and languages, that starting speed matters. The company publicly documents integrations with more than 100 HR systems, states ISO 42001 and SOC 2 among its compliance frameworks, and reports serving over two million employees across 60-plus countries.

It is also strong on the talent-marketplace side of the category. Matching people to internal jobs, projects, and mentors from an inferred profile is exactly what an inference engine is good at, and 365Talents pairs that with career-path recommendations and skills forecasting. If your problem is mobility at scale in a workforce that is largely knowledge work, and your HR data is rich enough to infer from, that is a real capability, not a demo trick.

The first divergence is what a skill record is. In 365Talents a skill on a profile is an inferred or self-declared signal, refreshed by AI. In SkillsDB it is a graded record: a proficiency level on an anchored scale, the method that produced it (self, manager, practical test, evidence), the date, and, for perishable skills, an expiry. SkillsDB can start the same way 365Talents does, by importing CVs and HRIS data to bootstrap a profile, but the profile then moves into an assessment loop. Inference gets you started; assessment tells you where you actually stand. See Skills Assessment for the six methods and what each is worth.

The second divergence is scope. 365Talents is a skills map plus a marketplace on top of it. SkillsDB is the operating record beneath the map: a competency framework written in the organization's own language, assessments against it, gap analysis per person and per role, a training matrix that runs on trained dates and expiries, development plans that target a level, and succession views computed from the same data. Those are the things an auditor, a plant manager, or a resource planner asks for, and a matching engine does not produce them. Proficiency Levels explains why the anchored scale is what makes the rest comparable.

The third divergence is fit. Both platforms are enterprise-grade on paper. SkillsDB is SOC 2 Type II certified and GDPR compliant, offers a GraphQL API with SSO and SCIM, and has multi-language support. 365Talents states SOC 2 and ISO 42001 and publishes a trust center. The practical difference is where each earns its keep: 365Talents in large, mobile, knowledge-work populations where inferred profiles are good enough for matching; SkillsDB wherever a skill has to be proven, tracked to a date, or defended in a review.

• Choose 365Talents if your first problem is an internal talent marketplace across tens of thousands of knowledge workers and an inferred profile is sufficient to match on.
• Choose 365Talents if you want AI to maintain the skills inventory with minimal manager involvement, and you are not yet ready to run structured assessments.
• Choose 365Talents if European data residency and multi-entity HR-system sprawl are the deciding constraints.
• Choose SkillsDB if you need proficiency you can act on: graded levels with method and date, per person, per skill, that feed gap analysis, training matrices, and development plans.
• Choose SkillsDB if any part of the workforce is regulated or safety-critical, where competence has to be evidenced against a revision and an expiry, not inferred.
• Choose SkillsDB if you want the framework in your own language, mapped to your roles, rather than an AI-generated ontology your managers have to translate.

The two are not mutually exclusive, and the sequence is the same one SkillsDB uses internally: bootstrap, then verify. An inferred map from 365Talents, or from SkillsDB's own CV and HRIS import, gives you coverage on day one. Assessment in SkillsDB then turns the parts of that map that matter into graded records. Most organizations find the verified set is smaller and more useful than the inferred set, and that the delta between the two is itself a finding.

Integration runs through the API on both sides. Inferred skills and role data come in, assessed levels, gaps, and trained dates go back out to the HCM or the marketplace. If you already run 365Talents for mobility, SkillsDB becomes the place where the skills behind those matches get measured. See Skills Intelligence Platform for the five capabilities a platform has to cover and where a marketplace stops.

• How is a skill on a profile produced, and can I see the method and date behind any single record?
• Can a manager or assessor override an inferred level, and is that override the record of truth from then on?
• Does the proficiency scale carry behavioral anchors per level, and is it the same scale across every skill?
• Can I produce, for one role, everyone currently qualified against the current revision with evidence, without exporting to a spreadsheet?
• Is the competency framework written in our language and structure, or generated from a vendor ontology we then have to maintain?
• What happens to a person's skills record when the AI model changes?