Industries

Bring AI-Enabled Products to Market, Compliant from Day One

For manufacturers and life-sciences companies whose product contains a model: GDPR and UK obligations, data integrity, and the technical documentation your notified body and your enterprise customers will read.

GDPRUK GDPREU MDRISO/IEC 42001SOC 2DATA INTEGRITY
PRODUCT LIFECYCLE, WHAT ATTACHES WHERESIX STAGES
01DataPROVENANCE · LAWFUL BASIS · RETENTION
02TrainDATA INTEGRITY · VERSION RECORD
03ValidateEVALUATION EVIDENCE · INTENDED USE
04LaunchTECHNICAL DOCUMENTATION · NOTICES
05MonitorPOST-MARKET PERFORMANCE · DRIFT
06UpdateCHANGE CONTROL · RE-VALIDATION
The obligation under each stage is what you have to be able to show for that stage, not when the work happens.

The reality

Two Regulators, One Product, No Sequencing

A device or platform entering European markets faces privacy obligations and product obligations at the same time, assessed by different bodies on different timelines. Data integrity expectations reach into how training and validation data were handled. And the questions arrive at the worst moment, during market entry, when the launch date is already committed.

Where the product makes or supports a decision about a person, the AI-specific obligations layer on top rather than replacing anything.

The tension

“We Validated It Once” Is No Longer an Answer

A model inside a product isn’t a static component. Performance drifts as populations and inputs shift, updates change behavior, and the evidence you produced at launch describes a system that has since moved. Regulators and customers are converging on the same question: what is your ongoing evidence that this still performs as claimed, for whom, and how would you know if it stopped.

Answering that after launch is expensive. Designing for it beforehand is mostly documentation discipline.

How we help

Privacy, Security, and AI Governance around the Product

GDPR and UK Readiness

Lawful basis, DPIAs for the model’s processing, transfer mechanisms, and notices that describe what the product actually does.

AI Governance for a Product Context

ISO/IEC 42001-aligned lifecycle controls: change management, evaluation, monitoring, and the record of decisions.

Data Integrity

Provenance, handling, and retention for training, validation, and post-market data.

Security for the Platform

Architecture review, access design, testing, and the SOC 2 or ISO 27001 program your enterprise customers ask for.

Documentation

The pack your notified body, auditor, and largest customer each need, written once.

Proof

A Product Cleared for Two Markets

Case study

GDPR for an AI/ML Medical Device

A manufacturer using AI to interpret ultrasound images planned an EU and UK launch. Our privacy team assessed existing policies and practices, made tailored recommendations, and revised the policies GDPR reached, so the launch proceeded with the data-handling position documented.

Launch with the Evidence in Place