AI use cases in medical device development
Medical device and life science teams use AI for the search, cross referencing and drafting work inside design control, risk management, verification, technical documentation, audit preparation and quality processes. In every case the regulatory decision stays with a person.
For taking a demo with our team.
The challenge
The work that quietly eats the week
None of this is the interesting part of the job, and all of it is where the hours go. Navigating cross linked projects. Finding the right information across a complex project takes longer than reading it does. Manual traceability reviews. Identifying coverage gaps across a full lifecycle means configuring reports and reading them line by line. Cross referencing standards by hand. Mapping a technical file to a standard takes weeks and comes out differently depending on who did it. Context switching. Moving between views and reports breaks concentration and slows the whole team down.
Our solution
Six jobs where AI takes the manual half
The pattern is the same in each one. The AI produces a reviewable proposal and the qualified person keeps the decision. Design control. Impact analysis across linked requirements, risks and tests when a design input changes. Risk management. Risks with no mitigation and mitigations with no verification, assessed against ISO 14971. Verification and validation. Test cases drafted from a requirement and linked back to it and to its associated risks. Technical documentation. Structured design artifacts generated from your product data and presented for review. Audit preparation. A clause by clause gap list, exportable as CSV so it can be reviewed offline. Quality processes. Related records surfaced for a CAPA or non conformance, with the investigation structure drafted.
Start where it costs you most
Every use case runs on your existing project structure, so there is nothing to migrate before it is useful.
Design Control and Impact Analysis
Ask what a change touches and get the answer with the links attached, instead of tracing it by hand.
Learn moreRisk Management
Coverage you can prove. Every risk without a mitigation and every mitigation without a verification, named.
Learn moreTechnical Documentation
Reviewable content generated from the product data you already hold, aligned to the standards you work to.
Learn moreCompliance Checker
A structured gap list against the standard, produced in a fraction of the time a manual review takes.
Learn moreMatrix Mind
Traceability and gap questions answered in plain language, grounded in the live project.
Learn moreMatrix Quality
AI inside the quality processes themselves, from document control through CAPA and audit preparation.
Learn moreFAQ
01Which AI use case do most teams start with?
Traceability and gap detection. The manual version of that job costs the most hours and the result is the easiest to verify, so it is the quickest way to judge whether the tool is doing what it claims.
02Do we need to change our process to use AI?
No. The AI works inside the project structure you already have, and the approval steps in your procedures stay where they are. The AI produces a proposal, and your existing review and approval flow handles the rest.
03How long before a team gets value?
The assistant works on your existing project data, so there is no separate setup and no content to migrate before it is useful.
04Does it work across more than one project?
Yes. Matrix Mind can assess a risk management file across several projects in a product portfolio at once, rather than one project at a time.