Human judgment leads. AI helps it scale.
NeoWise is expert-driven and AI-augmented — not AI-first automation. When it comes to something as consequential as recognizing a person's skills, that distinction isn't a tagline. It's the whole model.
Why this matters
Skills evidence — critical thinking, creativity, collaboration — is nuanced. It shows up differently in a classroom project than in a certification exam, differently across cultures, disciplines, and contexts. Reducing that nuance to a fully automated evaluation would be faster. It would also be wrong more often than institutions, employers, and the people being assessed can afford.
So NeoWise built its methodology the other way around: AI is a tool that amplifies expert judgment, not replaces it.
Our commitments
Expert-in-the-loop, always
The importance of having experts-in-the-loop, not just humans-in-the-loop, cannot be overstated. Every skills-evidence determination NeoWise supports is reviewed and validated by people with deep human skills expertise — not generated and released without expert review. AI accelerates analysis; it does not make the final call on what a person's evidence means.
AI-augmented, not AI-first
NeoWise's methodology — the Human Skills Framework and Skill Mining process — was developed through 15+ years of psychometric research, not trained into existence. AI is applied on top of that expert methodology to analyze existing assessments at scale, surfacing evidence that's already there rather than generating new judgments from scratch.
A note for our European partners
We know institutions and platforms working in the EU are evaluating AI vendors against a higher bar right now, including the EU AI Act's requirements for high-risk AI use in education — human oversight, transparency, data governance, and accuracy among them. NeoWise's expert-in-the-loop model exists for the same reason those requirements do: decisions that affect people's education and career paths deserve a human being accountable for them. We're happy to discuss our approach in detail with partners navigating these requirements.
What this means for you
Whether you're a platform adding a skills-reporting layer, or an institution making a credentialing decision — you're not adopting a black box. You're adding a methodology built by a recognized expert, amplified by AI, and checked by people at every step that matters.
AI Approach