Use case
Design change
A design change landed. Do you know every document that no longer holds?
The challenge
The change is committed. Whether it starts from a design input, a requirement, a specification, a performance target or a design output, a dimension, a material, a configuration - the ripple moves through the file differently.
A design input change can invalidate the verification chain: the test that proved conformance may no longer cover what it claims. A design output change touches the BOM, risk file, IFU, and protocols. Either way, updating every affected document by hand means one gets missed. The contradiction sits there until someone finds it.
How our solution helps
Change ripple detection.
When a design change lands - at the input or output level - our AI companion "Flurina" surfaces every downstream document now inconsistent with it. For input changes, it flags affected verification links. For output changes, it catches BOM, risk file, IFU, and protocol gaps. You update on purpose, not from memory. Change once, see everything it touches. The file stays true to the product.
What it costs when the file drifts
~15
downstream documents one design output can ripple through
50%
more spent on maintenance and re-certification over a five-year cycle
4 months
of a year spent keeping the file aligned as the product changes
Sources: EU MDR; MedTech Europe MDR/IVDR Survey (2025)
FAQ
Any questions? We’re happy to help.
What does it check after a design change?
The full ripple: input to output. For design input changes, it flags affected verification links. For output changes, it catches BOM, risk file, IFU, and protocol gaps.
How fast do we see the impact?
As you work, not the night before a gate.
Does it touch our PLM or design tools?
No. It reads the documents in your system e.g. SharePoint. No migration needed.
See where your file actually stands
Take your most recent design change. List the downstream documents you remember updating. Now check whether anything else referenced the old value and still does.
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