The EU AI Act (Regulation 2024/1689) requires organisations that deploy AI to maintain a demonstrable register, risk classification, technical documentation and human oversight. We build the platform in which you manage all of this centrally, tailored to your AI portfolio, your governance and your auditors.
The AI Act (Regulation 2024/1689) has been in force since August 2024 and is being phased in until August 2027. It is the world's first comprehensive AI regulation and works on a risk-based model: unacceptable risk is prohibited (government social scoring, real-time biometric identification in public spaces, emotion recognition in the workplace), high risk is heavily regulated, limited risk carries transparency obligations, and minimal risk faces hardly any requirements. High-risk AI comes with strict obligations: an AI system register, a risk management system covering the entire lifecycle, data governance with bias controls, technical documentation, logging, transparency towards users, human oversight, cybersecurity requirements, CE marking and registration in the EU database.
Generic GRC and privacy tools (OneTrust, Holistic AI, comparable suites) are often strong on the legal layer, but they rarely align with the ML process itself: how models are trained, which datasets go in, which metrics signal drift, how human-in-the-loop fits into the production flow. We build the piece that sits between your AI engineers, your compliance officer and your board, either as the core of your AI governance or as a specialised layer alongside existing tooling. For the broader strategy, this ties in with our approach to enterprise AI.
If you bring the AI system to the European market as a product, the requirements of the Cyber Resilience Act also apply: reporting deadlines, security updates and a component inventory. We set up the documentation so that you maintain it once and can use it in two places.
Depending on where you stand: just starting to take inventory, midway through classifying your first high-risk system, or working on a full governance platform for your entire AI portfolio. We advise which variant suits you in the first working session.
A central register of all AI systems in your organisation: purpose, dataset, model version, supplier, owner, risk category and compliance status. The starting point for every AI Act implementation and the query many organisations search for, rightly so, because without a register you don't know what the law applies to.
On top of the register: a practical risk assessment flow from project start to decommissioning, classification into unacceptable/high/limited/minimal, and a dashboard where the board and compliance officer see the status of each system at a glance. Includes a technical file vault and model cards.
Mission-critical platform with bias monitoring, drift detection, human-in-the-loop workflows, incident management, vendor management for third-party AI, and integrations with your ML stack (MLflow, SageMaker, Vertex AI, Azure ML). Suited to organisations with dozens of AI systems, regulated sectors or a pronounced board-level governance question.
A production-ready AI Act platform, plus everything around it so that your compliance team, AI engineers and auditors can operate it independently.
Four situations in which we support organisations. If you recognise one of these patterns, we would be happy to discuss the approach with you.
Recruitment, credit assessment, education, critical infrastructure, law enforcement, biometrics, migration or justice. The AI Act imposes its most stringent obligations here: a register, technical documentation, human oversight, CE marking and EU registration.
You can still manage one or two AI systems in Excel. At ten or more, version control, data governance and classification become unmanageable without a central system that connects to your ML stack.
DNB, AFM, AP, ACM or the Health and Youth Care Inspectorate will examine AI systems alongside sector-specific rules. A demonstrable register and risk management system is then practically essential to get through an audit.
Directors can be held liable for AI-driven decisions. A dashboard showing the current compliance status of each system lets them discharge that responsibility without relying on verbal updates from the data science department.
AI system register. The heart of your platform. For each AI system we record purpose, owner, supplier, datasets, model version, deployment location, business impact and risk category. Dynamic fields depend on the category: a high-risk system requires considerably more documentation than a minimal-risk chatbot. The register is searchable, exportable in audit formats and can be connected to your CMDB or MLflow instance.
Risk assessment flow. A structured wizard that guides a new AI project from idea to deployment. At each stage it asks the right questions, automatically classifies the system as unacceptable, high, limited or minimal risk, and includes a gate that prevents a system going live without completed documentation. For high-risk systems this includes a Fundamental Rights Impact Assessment (FRIA) under Article 27.
Documentation vault. Version-controlled storage for technical documentation (Article 11), data sheets, model cards, training data overviews, evaluation reports and declarations of conformity. Templates for the standard formats supervisors expect, with version history and a sign-off process for each document.
Human-in-the-loop module. Configurable review workflows for decisions made by high-risk systems. For each use case you determine which decisions may be automated, which require human sign-off and which should be escalated. Includes SLA tracking, queue management and a complete decision audit log for later reconstruction.
Monitoring layer. Drift detection on input features and output distributions, fairness metrics per protected group, accuracy tracking against benchmarks, and alerts for your data science team. We integrate with MLflow, SageMaker Model Monitor, Vertex AI Model Monitoring or a custom pipeline, depending on your stack.
Incident and post-market monitoring. Logging of serious incidents in line with the AI Act reporting obligation, root cause analysis, corrective actions and reporting flows to your national supervisory authority. For ongoing post-market monitoring per system, we build the automatable part; the legal part remains with your compliance team.
Vendor management. For third-party AI systems, such as a purchased recruitment tool with an AI component or a SaaS supplier using LLMs, we register the supplier, their declarations, their classification and the risks for your organisation. When a contract is renewed, the platform triggers a fresh assessment.
The AI Act affects every organisation deploying AI in the EU, but the impact varies considerably by sector. These are four groups we often work with.
AI in credit assessment, fraud detection and life insurance pricing almost always falls under high-risk. It also overlaps with DORA (operational resilience) and sector rules from DNB and AFM. We link AI Act compliance to your existing risk management without duplicate administration.
CV screening, video interview analysis and skills matching: these applications are explicitly listed in Annex III as high risk. This applies both to your own recruitment tooling and to the tools of your suppliers. A register plus vendor management is therefore practically indispensable.
Almost every AI application in the public sector touches high-risk domains: educational assessment, justice, migration, social services and critical infrastructure, and in healthcare the overlap with the MDR. In addition, transparency requirements around automated decision-making toward citizens often apply.
If you supply AI functionality to other businesses, you are often a provider under the AI Act and bear the heaviest obligations. For SaaS companies selling to enterprise clients, a demonstrable register and technical file has become a sales requirement; your clients will ask for it during their own audits.
Together we map which AI systems you currently have or are building, which suppliers are involved, which processes depend on them, and where the greatest risks lie. For organisations without an existing register, this is often where the real surprises emerge.
A working session with your compliance officer, data science lead and business owners. We map your AI systems to the AI Act categories, link them to GDPR overlap, and determine which modules are in scope for the first release.
A working build every two weeks. First the register and classification flow, then the documentation vault and audit log, then monitoring and human-in-the-loop. Your team tests along the way, and your compliance officer gives feedback on the legal conformity of each module.
Phased rollout per business unit, training for compliance and engineering teams, and ongoing management for security patches, regulatory updates and extensions. The AI Act will keep evolving in the coming years, and your platform needs to keep pace.
What organisations typically want to know before starting an AI Act implementation.
A no-obligation introductory call of half an hour. We listen to your AI portfolio, your governance question and your deadlines, and give direction on a platform that fits. Related topics: DORA compliance software, KYC/AML compliance software and custom risk management software. For automation around AI decision-making, this aligns with AI agents.
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