Enzai MCP server
Connects to your AI.
Any MCP-compatible agent gets the same governed connection, right where your teams already work.
Some of our integrations
Workflow tools
Jira, ServiceNow
Model providers
Anthropic, OpenAI
Agent tools
Copilot Studio, Claude Enterprise
Development environments
Azure AI Foundry, Amazon Bedrock, Databricks

AI risk and compliance

Assess each AI system against the rules.

Assess each AI system against the rules.

Close the gaps.

Close the gaps.

Start from frameworks such as the EU AI Act, ISO 42001 and NIST AI RMF, follow each risk until it’s mitigated, and export the results as a report.

Start from frameworks such as the EU AI Act, ISO 42001 and NIST AI RMF, follow each risk until it’s mitigated, and export the results as a report.

Reading a framework is the easy part.

Reading a framework is the easy part.

Reading a framework is the easy part.

Scope

Not every rule applies

Not every rule applies

A support chatbot and a model that prices health insurance face different obligations. Working out which controls fit which system is slow, manual work.

Mitigation

Risks get logged, then left

Risks get logged, then left

A review finds a risk and adds it to a spreadsheet. Whether the fix was made goes unchecked.

Audit

Gathered by hand, every time

Gathered by hand, every time

Test results, policies and sign-offs sit in shared drives and chat threads until someone chases them before an audit.

Turn a framework into work you can finish.

Turn a framework into work you can finish.

Turn a framework into work you can finish.

01

Assess

01

Assess

Work through the controls that apply.

Pick a system and a framework, such as the EU AI Act

Classify the system first, so the assessment only includes the controls it needs

Assign controls with due dates, then approve them or request changes

02

Mitigate

02

Mitigate

Take each risk from scored to mitigated.

Keep risks in one register, scored by impact and likelihood

Add mitigations and track them from not started to completed

Record the work done, with links, notes or files as proof

03

Report

03

Report

Show progress without building a deck.

Dashboards for assessments, risks and deadlines, filtered by AI product

See which assessments are due soon, and which are overdue

Export assessments as internal or external reports

01

Assess

Work through the controls that apply.

Pick a system and a framework, such as the EU AI Act

Classify the system first, so the assessment only includes the controls it needs

Assign controls with due dates, then approve them or request changes

02

Mitigate

03

Report

Before the fix, and after.

Before the fix, and after.

Before the fix, and after.

Each risk is scored before treatment and again after it.

Why it matters

Compliance with AI rules isn’t a one-time sign-off. For a high-risk system, the EU AI Act treats risk management as a process that runs for the system’s whole life, with regular review.1 Its provider must keep the technical documentation for ten years after launch.2 Once those rules apply, from December 2027, breaking them can cost up to 15 million euros or 3% of worldwide annual turnover.3 The record has to keep pace with the work.

Questions buyers ask

Questions buyers ask

Questions buyers ask

What is AI risk and compliance management?

AI risk and compliance management is the work of checking AI systems against the laws and standards they fall under, treating their risks, and keeping evidence that the work was done. It turns frameworks like the EU AI Act into tasks with owners and deadlines.

Which frameworks does Enzai cover?

Enzai runs assessments against the EU AI Act, ISO 42001 and NIST AI RMF. You can also build your own, such as an internal AI policy, with its own controls and classifications.

Does using Enzai make us compliant?

Enzai does the organizing: assessments, risks and evidence in one place, with your reviewers approving the work. Whether you meet a law or pass an audit is for your auditors and regulators to decide.

What counts as evidence?

It depends on the control: a completed form, a document, or metrics recorded on a system or its models, which fill in automatically. For risks, evidence is the links, notes or files that show a mitigation is done.

How are risks scored?

Each risk is scored by impact and likelihood, before and after treatment, so you can see what a mitigation changed. The register shows both, side by side.

What happens when a framework changes?

The assessment shows a new version is out, and you switch when ready. Keep your existing responses or start from scratch, and new or updated controls are marked.

Where each AI system stands.

Where each AI system stands.

Where each AI system stands.

Down to the last control.

Down to the last control.

Down to the last control.

Book a demo and we’ll show you how to assess one of your AI systems, work through its risks and export the report.

Book a demo and we’ll show you how to assess one of your AI systems, work through its risks and export the report.