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Our story

Why Entercept was built

Four observations that turned into a company. None of them were about AI capability, and all of them were about what happens when nobody can check the claim.

How Entercept started

  1. 01

    Regulation arrived faster than assurance

    The EU AI Act, UK GDPR and a growing stack of sector rules now place real obligations on organisations deploying AI in consequential decisions. The duties landed. The infrastructure for demonstrating they are met did not arrive with them.

  2. 02

    Self-attestation stopped being enough

    Most AI governance still rests on the builder assessing their own system. That is a reasonable place to start and a poor place to finish. When a regulator, an auditor or an enterprise buyer asks for proof, an internal questionnaire is not proof.

  3. 03

    Checkbox compliance obscures real risk

    Frameworks completed as paperwork produce documents that satisfy a process and tell you nothing about how a system behaves at the edges. The failures that matter show up in behaviour, not in policy.

  4. 04

    So we built the assessment layer

    Entercept exists to test AI systems independently, capture what is actually observed as verifiable evidence, and issue a report that holds up under scrutiny from a supervisor, an auditor, a customer or a court.

Where that leaves us

An assessment layer, not another framework

There is no shortage of guidance on responsible AI. There is a shortage of people willing to test a system and put their name to the result.

Entercept assesses AI systems that make or materially influence consequential decisions, and issues reports that hold up when someone pushes back. That is the whole company. We publish a full specimen report, including its non-compliant conclusion, because an assurance provider that only shows clean results is not showing you anything useful.

Read the specimen report (opens in a new tab)
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