Understand your AI Act obligations.
Prove compliance.
Keep it aligned as AI evolves.

A practical compliance platform for companies deploying AI in the EU and the consultants who support them. Built around real deployments, not abstract models.

Join 300+ professionals already exploring AI Act compliance with Aigolex

The real AI Act problem

Companies don't know if they are AI providers, deployers, or both.

Obligations depend on how AI is used, not on the model itself.

Documentation becomes outdated as soon as systems or vendors change.

Audits, enterprise customers, and boards expect immediate answers.

AI Act compliance is not a one-time exercise.
It's an operational problem.

Compliance attaches to deployments, not to AI models

That's why the platform mirrors the structure of the AI Act itself

Company

the legal entity ultimately responsible for compliance

Workspaces

distinct operational perimeters where AI is developed, tested, or used

AI assets

the underlying AI systems or models, independent from any single feature

Deployments

how those AI assets are actually used in practice, by whom, and for what purpose

Under the AI Act, obligations, risk classification, and roles attach to deployments not to AI models in isolation. This ensures compliance decisions reflect real-world AI use, not theoretical system descriptions.

Scope

Define where AI exists, how it's used, and who is responsible.

•Maps AI usage across companies and workspaces
•Identifies AI assets and their concrete deployments
•Determines your role under the AI Act (provider, deployer, or both)

Misclassifying your role means misapplying every obligation that follows.

Obligations

Know exactly what the AI Act requires, per deployment.

•Assigns regulatory requirements at the deployment level
•Based on role, risk classification, and usage context
•Generates clear, trackable checklists
•Separates applicable obligations from irrelevant ones

The AI Act is obligation-driven. Guessing is not a strategy.

Evidence

Always-ready documentation to prove compliance.

•Centralizes compliance documentation per workspace and deployment
•Includes system descriptions and risk assessments
•Tracks human oversight measures and monitoring controls

Static documents fail the moment reality changes.

Continuity

Stay compliant as AI systems, vendors, and uses change.

•Monitors changes to AI assets, deployments, and operational perimeters
•Flags when obligations or risk levels must be updated
•Alerts when documentation needs to be refreshed

Most compliance failures happen after the first assessment.

AI Act compliance readiness assessment

Identify your AI Act obligations, classify risk exposure, and uncover compliance gaps — with a guided interactive assessment.

Built for teams that can't ignore regulation

EU-based or EU-operating

Active AI deployments

Exposure to audits

Legal & compliance leaders

Risk & trust teams

Engineering leaders accountable for AI systems

Built by people who've done this before

Experience in legaltech and regulated environments

Built with legal and technical teams

Not Big-4 complexity

Prepare now. Don't scramble later.

AI Act

What problems does the AI Act aim to solve?

Aigolex Team7 March 2026

In recent years, artificial intelligence has moved from experimental technology to infrastructure used in many economic sectors.

Companies use AI systems to analyze large amounts of data, automate tasks, and support strategic decisions.

This evolution has brought new opportunities, but also a series of risks that have attracted the attention of legislators.

It is precisely to address these critical issues that the Artificial Intelligence Act was introduced.

The problem of algorithmic discrimination

One of the most discussed risks concerns the possibility that an AI system produces discriminatory results.

This can happen when the data used to train the algorithm reflects biases already present in reality.

In these cases, the system can amplify these distortions instead of correcting them.

Transparency and accountability

Another problem concerns the difficulty in understanding how some AI systems make decisions.

Many advanced models function as true "black boxes", making it complex to explain why a particular decision was made.

The AI Act therefore introduces rules aimed at improving transparency and accountability in the use of artificial intelligence.

Conclusion

The goal of the regulation is not to limit innovation, but to create a framework of trust that allows companies to develop and use AI systems in a safe and responsible manner.

Understand your AI Act obligations.Prove compliance.Keep it aligned as AI evolves.