Cupelcupel.foundation

A common layer for professional trust

Cupel is an open framework that connects the systems already used to verify competence — so that human expertise is recognisable in an AI-saturated world.

The problem

Credentials used to show what people could do. Now, they often show what machines can produce. AI can pass the CFA Level III. It can pass the bar. It can generate the signal of competence without the substance.

The market responded by creating more credentials — the U.S. went from 334,000 in 2018 to 1.85 million by 2025. But more isn't better. Gartner forecasts that one in four candidate profiles could be entirely AI-fabricated by 2028.

Five separate systems already support professional trust: identity verification, skills assessment, digital credentials, content authenticity, and reputation. Each works on its own — but they don't connect. There's no shared way to describe, compare, or verify proof of real competence across them.

We don't need new systems. We need a common layer that connects the ones we already have.

The five trust signals

No single signal is enough. Cupel looks at all five together — which makes the overall picture much harder to fake.

01
Credentials
Certificates and diplomas from accredited institutions — verified against the issuer's registry.
02
Assessments
Verified test scores and practical evaluations that demonstrate what someone can actually do.
03
Outcomes
Real work results: projects delivered, decisions made, measurable impact — not just claims.
04
Peer verification
Endorsements from colleagues who witnessed the work and can be held accountable for their assessment.
05
AI audit trail
A record of how AI tools were used, where human judgment was applied, and who was responsible for key decisions.

What Cupel is

Cupel is an open framework — a vocabulary, a data format, and a set of guidelines — not a platform. Any credential issuer, assessment body, or HR platform can participate without changing their core infrastructure.

  • —A common vocabulary for the five trust signal types, so different systems can describe competence in terms each other understands.
  • —A lightweight data format (JSON-LD, compatible with W3C Verifiable Credentials) for expressing and linking these signals.
  • —Evidential weight guidelines — how much trust to place in each signal type, based on how easy it is to game.
  • —Standard mappings to C2PA, W3C VC, Credential Engine, and 1EdTech, so platforms can integrate gradually.
On privacy: Cupel is designed for selective disclosure. Participation is voluntary, and individuals choose what signals to share and with whom. The framework has no central registry of people.

The project is open-source (AGPL-3.0) and trademark-protected (UK IPO No. UK00004352899). “Cupel-conformant” means meeting published technical and ethical criteria — just as Linux or OpenID use open technology with protected names.

Who we invite

Implementers
Connect your existing credentials or assessments to the Cupel taxonomy. You don't need to adopt everything at once.
Standards bodies
Work with us on mappings between Cupel and your specifications — W3C, C2PA, Credential Engine, 1EdTech, and others.
Researchers
Help build the evidence base for what makes a professional signal trustworthy, especially in human–AI collaboration.
Practitioners and employers
Share what genuine competence looks like in your field. Your insight shapes the framework.