Efficient Compliance Management Without the Overhead

In brief

Governance programs fail when frameworks and regulation are managed in silos instead of a shared system of requirements, risks, controls, and evidence. Trail keeps every framework you're subject to in one place, so a single piece of evidence can satisfy a GDPR record, and an EU AI Act obligation at once.

With trail, your organization can:

• Manage multiple frameworks from one data model: Requirements from any regulation or standard, or internal policies all link back to the same asset, while making use of existing risks, controls, and evidence - so nothing has to be duplicated.
• Adopt curated, expert-maintained frameworks: Work with trail’s built-in libraries for major regulations (like the EU AI Act) and standards (like the ISO/IEC 42001), which are kept current as the underlying regulation or standard evolves.
• Build and maintain custom governance frameworks: Create your own frameworks with your own requirements and controls, and mapped to the right responsibilities.
• Track compliance status live: See requirement-by-requirement status across every framework you're subject to as well as for each individual asset.

The core challenge: effective compliance without duplicate work

Regulatory requirements and industry standards look independent on paper, but in practice they overlap constantly – especially when it comes to AI. As a result, the same underlying work gets repeated for every regulation or standard.

Trail’s data model is built around assets (models, systems, use cases, vendors, or agents) that carry their own risks, controls, and evidence. Frameworks sit on top of that, as sets of requirements mapped to governance objects. Fulfilling a requirement in one framework (e.g. the EU AI Act) through a control and respective evidence automatically shows that same fulfillment status wherever that control is relevant to another framework (e.g. your internal AI policy). This means: you do the work once, and every relevant requirement is updated.

Managing the EU AI Act in trail

As the EU AI Act has become a foundational framework for most AI-driven organizations – often described as "North Star" when it comes to AI compliance – trail supports specific features and content around it by default: risk and role classification shows users which EU AI Act requirements apply, which then triggers recommendations for expert-curated controls. As a result, you do not need to manually work through the regulation for every new use case and get a guided workflow out-of-the-box. As roles can shift (for example, when an organization's modifications to an AI system makes them become a provider instead of e.g. a deployer), trail flags when a use case's classification may shift your compliance requirements.

Not sure how a specific use case classifies? Try our EU AI Act self-assessment.

Managing GDPR in trail

Most AI governance work touches data protection at some point, and often data privacy teams are even driving such AI governance initiatives. Training data, model outputs, vendor sub-processing, automated decision-making, etc usually subject to various regulation, both from a data privacy and product safety perspective. In the EU, the GDPR and the AI Act are strongly intertwined and complementary to each other.

trail supports, for instance, the compliance with the GDPR through questionnaire functionalities and the management of Records of Processing Activities (ROPA), linked to your assets and processes. This also supports Data Protection Impact Assessments (DPIAs), allowing you to trace which vendors and sub-processors are behind a given AI system, closing the loop between "what data are we processing" and "what AI system is processing it."

Managing standards in trail (e.g. ISO/IEC 42001)

For organizations pursuing certification for their whole AI management system in addition to frameworks on an asset-level, trail can provide the structure for governance frameworks on the organizational-level. Read more about how trail enabled management systems and certifications, e.g. for the ISO/IEC 42001.

For some of these standard, trail maps the requirements to curated control and risk libraries, with guided workflows for implementation and clear ownership assignment. Audit modes provide a dedicated view of approved requirements and attached evidence for internal or external auditors.

Building and managing custom frameworks

Many large enterprises have their own sophisticated frameworks or standards (SOPs) on how to govern certain IT or AI assets. This may include e.g. software validation processes, internal risk schemas, and information classification requirements, which should be ideally aligned with your other regulatory requirements and AI governance requirements to profit from synergy effects and avoid duplicated work.

trail’s custom framework builder lets you easily define your own set of requirements and map them to assets, assessments, risks, and controls. This means an internal policy requirement and an EU AI Act obligation can sit side by side on the same asset, assessed and evidenced through the same workflow, rather than living in separate trackers.

Our curated framework library already covers the frameworks most AI governance and modern GRC teams need - GDPR, ISO/IEC 27001 and 42001, the EU AI Act, and NIST's AI RMF are among them. But when a framework isn't in trail yet, you can add it yourself and request our team's help to add additional ones.

Ready to bring your frameworks into action?

Whether you need to demonstrate meet EU AI Act obligations, align your AI usage with the GDPR, follow a certain industry standard or track internal policy adherence, trail gives you one place to manage it all, without asking your team to document the same evidence in five different ways. Get in touch to see how trail’s compliance management fits your organization's needs.