Praxis
Engineering compliance for GDPR, the EU AI Act, the EU Data Act, and MiCA. The productised core of our Governance, Risk & Compliance service.
The Engineered-Compliance Solution
Engineered Controls for Regulated Environments
Praxis is the productised core of our Governance, Risk & Compliance service. Where most compliance work produces documents, Praxis produces working controls, continuous evidence, and audit-ready artefacts. Whether your systems meet a given obligation is determined by the regulator, but the substrate Praxis helps you build is the evidence they will look at.
We engineer the technical substrate that supports compliance across GDPR, the EU AI Act, and the EU Data Act, designed once and evidenced continuously. A single Article 32 control can support a GDPR obligation, an AI Act robustness requirement, and a Data Act access constraint. Built once, mapped across, and defensible in front of every supervisory authority that depends on it. For crypto-asset issuers and service providers in scope of MiCA, the same substrate extends to licensing, custody, and market-conduct obligations.
The Praxis Compliance Agent
At the heart of every Praxis engagement is a domain agent we build and operate on your behalf. It reads the live regulatory text alongside your own systems, policies, and code, and it runs continuously inside our delivery. Gaps surface as they appear, not at quarter-end. Evidence stays current as your platform changes. When a regulator asks, the pack is ready.
The agent does not replace your legal team or your compliance officer. It removes the parts of the job a machine should be doing, things like tracking which of your microservices logs which fields against which lawful basis, watching for the next ENISA opinion, or generating the artefact a supervisory authority will accept. Your specialists keep the judgement calls only humans should make. Our public thinking on this approach is laid out in the Regulatory Stack series and the launch piece, Engineered Compliance: Why the EU Regulatory Stack Belongs in Code.
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Where Praxis Engages
Our Approach
What Praxis Delivers
From regulatory text to running controls
Praxis spans the full path from regulatory interpretation to verifiable production controls. Each engagement scales to the obligations that apply to your organisation.
Regulatory Surface Mapping
Identifies which articles of GDPR, the AI Act, the EU Data Act, and (for crypto-asset firms) MiCA apply to your specific systems, data flows, and AI deployments. The starting point for every Praxis engagement.
Gap Analysis and Remediation Plan
Maps your current state against the applicable obligations. The output is a prioritised remediation roadmap with concrete engineering tasks, not a list of policies to write.
Control Implementation
Builds the actual controls, including Sentinel policy enforcement, Enclave deployments for sensitive workloads, cryptographic lineage, and consent-purpose enforcement in code.
Compliance Agent Inside the Engagement
We deploy the Praxis agent into the engagement with your corpus loaded. It surfaces gaps continuously, prioritises remediation, and tracks both regulatory and system change so your evidence stays current. The agent is operated by our team, not handed off as a product for you to install or maintain.
Evidence Pack Generation
Produces audit-ready evidence packs on demand, with cryptographic integrity and direct mapping to the obligations each artefact speaks to. Built for supervisory authority review.
Continuous Re-Attestation
In continuous engagements, we run ongoing verification against your live systems. Every deployment, policy change, and model update triggers re-attestation. Drift is surfaced as it appears, not at the next annual review.
Regulator Liaison and Translation
Translates between engineering reality and regulator expectations during inspections, supervisory authority correspondence, or conformity assessments. Optional, included in continuous engagements.
Cross-Framework Optimisation
Identifies controls that can speak to multiple frameworks at once, so you build once and evidence many times. Reduces both implementation cost and ongoing audit overhead.