saascode
analytics, bi & data·run 103 · May 2026

Inkjudge

A governed documentation workspace for model providers that maps sourced evidence to reviewed Article 53 records, machine-readable exports, signatures and versioned public disclosures.

Genesis score6.40/10
Make Inkjudge real.0/500
500 more votes and Inkjudge is authorized for build.
0%500 to authorize
Backing is the vote. When an idea crosses 500, we pull it into the build pipeline and ship it for real — the votes decide what gets built next, not an editor.
The opportunity
Aug 2026Enforcement milestone
The case

Organizations providing general-purpose AI models in Europe may need to assemble model descriptions, training-data summaries, compute information, evaluations and other records under Article 53. The supplied research confirms an August 2, 2026 enforcement milestone for relevant new models, a published voluntary Code of Practice and an official model-documentation form. Applicability and transition rules still depend on provider role, model date, systemic-risk status and current legal review.

Inkjudge inventories required claims, requests supporting evidence from accountable owners, maps each item to the current template and preserves reviewer decisions. It can emit human-readable and machine-readable records, but a signature proves origin and integrity only. It does not prove the content is complete, accurate, legally sufficient or accepted by an authority.

A proposed public well-known endpoint could make customer-approved disclosures easier to retrieve, but the supplied research does not establish it as an official or adopted standard. It must remain optional, clearly labeled and free of confidential material. A low-adoption public JSON schema confirms experimentation, not market consensus.

Evidence request, source submission, reviewer finding, legal applicability, approved disclosure, signature, publication, authority request, correction and outcome remain separate. The first release should support one model and one reviewed documentation form without automatic compliance scoring or regulatory filing.

Who pays — and why

Compliance, legal, model-governance or product leader at an organization reviewing whether it is a general-purpose AI model provider in Europe

What it unlocks
A requirement-to-evidence matrix separating legal applicability, requested claim, source owner, reviewer finding, approval and unresolved gap
Versioned human-readable and machine-readable documentation that preserves template, model, evidence and approval history
A bounded disclosure and correction trail separating signed integrity, public availability, authority acceptance and later outcome
How Genesis scored it
6.40across seven criteria
tension 7temporal 8blindspot 5buyer 5leverage 7convergence 5why-not 7
8
Temporal window

The supplied official sources confirm an August 2026 enforcement milestone for relevant new models.

7
Productive tension

Providers need fast documentation, while formal-looking automation can conceal missing evidence and overstate compliance.

5
Convergence

The record contains two cross-references and two inbound connections without a supplied cross-vertical cluster.

Why it scored well

The supplied primary materials confirm a near-term enforcement milestone, a published documentation form and an under-productized machine-readable documentation surface.

What's holding it back

The buyer and provider population are broad, legal applicability is complex, the proposed public endpoint is not a standard and no structural incumbent barrier is demonstrated.

Signals detected4 sources crossed
SignalSupplied EU AI Act Service Desk research

SignalSupplied official Code of Practice research

SignalSupplied repository review

SignalSupplied competitor scan

Direction briefinkjudge.md
inkjudge.md
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