Imagine having a digital security guard that watches your AI in real-time to make sure it doesn't make biased or illegal decisions. Instead of checking the AI's work weeks later, this system catches mistakes the moment they happen. It's like a black box for airplanes, but for AI, recording everything so you can prove exactly why a decision was made.
Companies using AI face massive legal risks and manual documentation burdens to comply with laws like the EU AI Act. Current compliance is often done after the fact, making it slow and prone to errors.
A platform that embeds real-time risk monitoring and automated evidence collection into AI infrastructure. It includes two validated methods for explaining AI decisions (black-box and white-box).
If you are a retail bank dealing with automated loan approvals — this project developed a monitoring platform that provides real-time explainability. This ensures you can justify every decision to regulators and avoid fines of up to 7% of global annual turnover.
If you are a diagnostic provider dealing with AI-driven patient screening — this project developed a system for bias mitigation and risk management. This ensures patient outcomes are fair and meet strict healthcare regulations.
If you are a government agency dealing with automated citizen services — this project developed an automated compliance evidence system. This reduces the manual work needed to document AI lifecycles for legal audits.
Based on available project data, specific pricing details are not provided, though the project received an EU contribution of EUR 2,490,000 for development.
Yes, the project aims to transform ad-hoc compliance into systematic, scalable practices and plans to scale across European markets, starting with the Netherlands and Germany.
Based on available project data, specific licensing terms are not mentioned, but the project is led by Deeploy B.V., an SME.
The platform provides real-time risk management and automated compliance evidence collection to help organizations avoid fines of up to 7% of global annual turnover.
The system integrates directly within the infrastructure where the AI models run, allowing for real-time monitoring and inference log archiving.
The project is led by a single Dutch SME, Deeploy B.V., with a 100% industry ratio. This lean structure suggests a highly commercial focus, aiming for rapid deployment and market entry rather than academic exploration.
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