AI eQMS for medical device and life science teams
An AI eQMS is a quality management system where the AI works on your live quality records rather than on documents pasted into a separate chatbot. Matrix Quality and Matrix Req do this under your existing access controls and audit trail, with human approval required before anything is written.
A chat window bolted onto a QMS is not an AI eQMS
AI as a function of the quality system itself
The term covers two very different architectures, and the difference surfaces the moment an auditor asks who decided and on what evidence.
It only sees what you paste. The assistant works on an extract, so its answer is already out of date and blind to everything it was not given.
Nothing lands in the audit trail. The reasoning behind a decision ends up in a chat log that sits outside your quality system.
Somebody retypes the output. That is where the time saving goes, and where transcription errors enter a controlled document.
Your controlled content leaves your controls. Access rules, retention and data agreements stop applying the moment it is pasted elsewhere.
Matrix Quality and Matrix Req put the AI inside the record, where it inherits everything the rest of the system already enforces.
It reads the live record. Answers reflect the current state of the quality system, including the change somebody made an hour ago.
It respects your permissions. People see what they are entitled to see. The assistant widens nobody's access.
It writes only through review. Output appears in a review interface and reaches your documentation only when a person confirms it.
It cannot alter or delete records. The AI has no capability to change existing data, so changes still go through your change control.
A chat window bolted onto a QMS is not an AI eQMS
The term covers two very different architectures, and the difference surfaces the moment an auditor asks who decided and on what evidence.
It only sees what you paste. The assistant works on an extract, so its answer is already out of date and blind to everything it was not given.
Nothing lands in the audit trail. The reasoning behind a decision ends up in a chat log that sits outside your quality system.
Somebody retypes the output. That is where the time saving goes, and where transcription errors enter a controlled document.
Your controlled content leaves your controls. Access rules, retention and data agreements stop applying the moment it is pasted elsewhere.
AI as a function of the quality system itself
Matrix Quality and Matrix Req put the AI inside the record, where it inherits everything the rest of the system already enforces.
It reads the live record. Answers reflect the current state of the quality system, including the change somebody made an hour ago.
It respects your permissions. People see what they are entitled to see. The assistant widens nobody's access.
It writes only through review. Output appears in a review interface and reaches your documentation only when a person confirms it.
It cannot alter or delete records. The AI has no capability to change existing data, so changes still go through your change control.
Where the AI does real work
Six quality processes where AI removes manual effort without touching the decisions that stay with a qualified person.
FAQ
An AI eQMS is an electronic quality management system in which AI operates directly on the live quality record, under the system's own access controls and audit trail, rather than through a separate chat tool working on pasted copies.
Matrix Quality covers life science quality processes and Matrix Req covers design control, risk and technical documentation. Both are part of Matrix One.
The question an auditor asks is who decided, on what evidence, and whether you can show it. Because every AI output passes through a human review step and the resulting change lands in the audit trail, the decision record looks the way it always did.
The validated step in your procedure is the human review, not the generation.
No. Approval is a human act carried out by a named, trained and authorised person, and the AI never holds that role. It proposes, and a qualified person disposes.
No. We do not train any model on customer data or on public data. Our AI agents use pre trained models from trusted providers under a zero data retention condition, so your data is never retained or reused.
Yes. AI features are additive to the platform and your team decides which of them are enabled.