Antefacts

What we do

We do not measure AI systems. We prove the measurement was honest.

Criteria are sealed and cryptographically committed before anyone is assessed. The scoring harness is published so any third party can rerun the evaluation and get the same numbers. Every evaluation carries a machine-checked record proving it was conducted exactly as it was committed to in advance.

The result is an assurance claim that does not require anyone to trust us, or to trust whoever ran the test.

We prove the process. We bound the result.
The problem

Attestation, not evidence

A corporate picks a supplier after a bake-off whose criteria were never published. A standards body names a preferred auditor after a workshop. A regulator is asked to accept a conformity assessment whose underlying test cannot be rerun. In each case the decision may well be right. There is simply no way for anyone outside the room to tell.

Antefacts builds the layer underneath, so that the working can be shown.

Assurance model

Two kinds of claim, never mixed

Most of this market sells one blurred assurance. We separate the two claims that can honestly be made, and we are explicit that only one of them admits proof.

Claim tiers
AxisWhat is claimedHowTier
Process integrity This evaluation was conducted in accordance with its own pre-registration, and its record is unaltered Machine-checked, on every evaluation Proved
Subject performance The system measured at a stated value, within a stated interval, under a stated configuration Pre-registered statistics, or pre-registered scoring Bounded Registered Never proved

Set out in full on the method page. No evaluation we run will assert that a system is proved safe, proved correct, certified or compliant. That restraint is not modesty. It is the only position that survives a technical assessor reading the method closely, and it is what makes the first claim worth anything.

Construction

Cryptographic, and deliberately not a blockchain

Every record is hash-linked, signed and timestamped by an authority we do not control, and the chain roots are published to independent locations so that we cannot quietly rewrite our own history. That is a hash chain in a database with independent republication: the boring, auditable construction. A distributed ledger would add nothing to the guarantee and a great deal to the doubt, so our specification prohibits one.

Mechanisms

What that changes

01

Commitment before assessment

Criteria, weights and pass thresholds are published and hash-committed before any subject is assessed. Nothing moves once the data arrives.

02

Held-back inputs

Subjects receive the requirement specification. They do not receive the scoring inputs in advance, and they are barred from retaining them.

03

Rerunnable by anyone

The scoring harness is published. A third party can obtain it, rerun the evaluation and check every hash without contacting us.

04

A record that resists rewriting

Append-only, hash-chained, independently timestamped, with roots republished where we do not control them.

05

A route to contest

Every participant may obtain the harness and rerun its own submission. A challenge is a defined record with a deadline and an outcome, and it enters the ledger whichever way it is decided.

06

Deviations on the record

Evaluations depart from plan. When ours do, the departure is recorded and published, including where the results themselves stay confidential.

What we offer

Two ways to use the method

Licence

For certification bodies

An annual licence to the method and the platform, co-branded. Your assessors run the evaluations, you issue the opinion, the evidence carries both names and survives an appeal. Built for the bodies that will assess high-risk AI under the EU AI Act from 2 December 2027.

Service

For procurement

A fixed-price evaluation of the two to four systems you are choosing between, on criteria you author and we seal before any vendor is seen. The losing vendors can rerun it. That is why they do not dispute it.

In production

The first instrument built on the protocol

Invigil, which measures the formal reasoning of frontier AI models on Lean 4 problems they have never seen, runs each quarterly holdout under this method. Its customers receive a measurement certified by a party other than Invigil. Invigil is under common ownership with Antefacts; what that means for our neutrality, and the rules that follow from it, are set out on the licensees and disclosures page.

Timing

Fifteen months

From 2 December 2027 a notified body's assessment of a high-risk AI system is a legal act. Providers appeal it, competitors contest it, notifying authorities review it. Bodies must have chosen a method before then, and bodies choose once. The timetable is on the certification bodies page and our reading of the regulation is in the notes.

Audience

Who this is for

Certification and notified bodies that need a defensible technical method for conformity assessment and have no intention of building one. Corporate procurement functions whose supplier selections have to survive challenge from the vendors that lost. Anyone whose signature ends up on a decision they cannot currently show the working for.

Release

What we publish, and when

The protocol specification, the scoring harness and the machine-checked development are given away. They are released as one bundle together with the first conforming evaluation, because a specification published alone is a document, and the four published together are a demonstration.

Already here: how the method works, what it does not buy, and the rules we hold ourselves to.

Etymology

The name

From the Latin ante factum, before the fact. An antefact is a thing fixed before the event it governs: the criteria, the weights and the thresholds, sealed before any data exists. That is the whole method in one word.