Best QMS for AI medical devices in 2026

AI-enabled medical devices are one of the fastest-growing categories in regulated health technology, and they sit in a particularly interesting compliance position. The underlying regulatory framework -- IEC 62304, ISO 13485, ISO 14971 -- applies to AI-enabled SaMD the same as any other medical software. But regulators in both the US and EU have added specific guidance on AI and machine learning that goes beyond the base standards.

Understanding the additional requirements is important. Choosing the right QMS to manage them is the practical starting point.

What is different about AI medical device compliance

The FDA's AI/ML-based SaMD action plan and the EU's AI Act (which overlaps with MDR for medical AI) both highlight a few areas that require specific attention beyond standard SaMD compliance:

Transparency and explainability: For AI-driven diagnostic or treatment support tools, regulators expect documentation of how the model reaches its outputs. This does not mean exposing model weights -- it means being able to explain the basis of a clinical recommendation at the level a clinician can evaluate.

Training data and validation: Your QMS needs to document what data was used to train the model, how the training set was validated, and how performance was evaluated on held-out data. These become part of your technical file.

Predetermined change control plans (PCCP): The FDA specifically allows AI/ML SaMD to include a plan for how the algorithm can be updated post-market without requiring a new submission for every model update. If your product learns or updates in the field, you need a PCCP.

Post-market performance monitoring: AI systems can drift over time as the population of users changes. Your post-market surveillance needs to account for model performance monitoring, not just traditional adverse event tracking.

What this means for your QMS

The good news is that the core QMS requirements are the same: documented requirements, verifications, test evidence, traceability, structured releases, risk analysis, non-conformance management. Your AI validation activities become part of the verification and test evidence record.

The additional AI-specific documentation -- training data, validation methodology, PCCP, post-market monitoring plan -- layers on top of the standard QMS. It does not replace it.

A QMS that handles the standard requirements well, and is flexible enough to attach additional technical documentation (AI validation reports, model cards, PCCP documents), is what you need.

The options

| Tool | AI-specific features | Free tier | Starting price | |---|---|---|---| | QualiHQ | Document attachment, requirements generation from AI product docs | Yes | Free | | Qualio | General document management | No | ~$500-800+/month | | Greenlight Guru | General document management | No | ~$1,000+/month | | MasterControl | Enterprise document management | No | Enterprise |

No QMS tool currently generates AI validation documentation for you. The AI-specific compliance artefacts -- model validation reports, training data documentation, PCCPs -- are things your team produces and attaches to the relevant records in your QMS.

QualiHQ

Handles the standard SaMD QMS requirements with AI generation from your product documentation. AI validation documents attach as supporting evidence to verifications and releases. The requirements generation understands AI/ML product descriptions and produces requirements that reflect transparency, validation, and performance monitoring obligations. Free to start.

Best for: AI/ML SaMD teams who need the standard QMS in place and want AI to generate the initial structure.

Qualio and Greenlight Guru

Both handle document storage and management well. Neither is specifically designed for AI/ML SaMD. Qualio is the stronger option for pure software AI products (no hardware). Greenlight Guru is stronger if you have a hardware component.

Best for: Teams with a quality manager and a compliance budget who want a more established enterprise platform.

The practical starting point

Get the standard QMS foundations in place first. Requirements, verifications, traceability, release management, risk analysis. Then layer the AI-specific documentation on top -- your model validation reports, training data documentation, and PCCP become documents in the system attached to the relevant records.

The teams that struggle most with AI medical device compliance are the ones that tried to solve the AI-specific parts before getting the underlying QMS right.

QualiHQ is free to start. Generate your initial AI medical device QMS from your product documentation. No credit card required.