Sift for Medical devices
Days of testing.
Evidence your team can use.
Bring device measurements, test conditions, and engineering findings from development, testing, and manufacturing into one shared workspace. Help engineers review their own runs, find events that need attention, and carry what they learn into the next test.
Find what deserves attention
in every long test.
Bring device measurements, test conditions, and engineering history into one shared record for the next design review.
Why did flow fall while commanded speed held?
Durability run 14 lost 8% of its flow near hour 62 while rotor speed held. Compare it with run 11, inspect the loop, and share the review.
Keep bench data, engineering findings, and review evidence connected as devices move from development into verification, production, and the field. Build on what’s already known and bring field learning back into design.
Development
Characterize how the device behaves and keep the baseline evidence for later verification.
Verification
Compare revisions and durability runs with earlier results, limits, and design context in reach.
Production testing
Apply established checks to every unit and trace results back to verification evidence.
Field investigation
Investigate returned devices with their test history available, and bring findings back into development.
Field findings inform development
For engineers
Get to answers faster.
For engineering leaders
Keep teams moving together.
For executives
See what’s ready.
Know what’s at risk.
Review long runs with earlier results and test conditions in reach. Reuse useful analysis and carry findings into the next test.
Standardize repeated reviews, share findings between R&D, test, and quality teams, and keep continuity from verification to production.
Bring verification progress, durability questions, and open findings into design reviews, so teams can prioritize the work that moves the device forward.
Proven on complex hardware programs.
These results come from adjacent engineering fields: autonomous rail, lunar rovers, and uncrewed aircraft. They are not medical-device outcomes.
Fits your stack.
Grows with your program.
Can our engineers keep using MATLAB and Python?
Yes. Engineers keep MATLAB and Python for their own analysis. Sift keeps console exports with the device, firmware, and procedure, and exports to CSV, Parquet, or MATLAB. Reports support the engineering review, and the decision stays with your team.
Can we compare durability runs across units and revisions?
Yes. Each run keeps its device, firmware, procedure, and operating conditions. Families align related runs to a shared reference point and compute the normal envelope, so a new run is compared against equivalent tests.
Can we bring in data from local or disconnected systems?
Yes. Consoles and DAQ systems on the bench often stay offline. Export the run when the test ends and import the file into Sift, where it joins the device, procedure, and earlier runs. Sift Edge can capture data locally where a connected workflow is needed.
Where can Sift run, and how is access controlled?
Sift runs as cloud SaaS, hybrid, or fully on-premises, including air-gapped environments, with the same capabilities in each. Access is set by asset, data set, and user group, and an audit log records every query. Sift Edge captures and views data beside the hardware, even offline.
Can we start with one repeated review?
Yes. Bring one representative test file and the checklist your team uses today. Sift engineers show how to make the data usable, compare related runs, and keep the evidence behind the decision. The same setup then extends to more benches and programs.
How should we measure the value?
Measure the workflow you start with: time from test completion to an engineering decision, review hours per run, and the effort spent maintaining data infrastructure. Sift customer stories report results in these terms, from review hours saved per engineer to infrastructure costs avoided.
Accelerate your hardware development
Start with the engineering question slowing your team down.
Bring a representative workflow, your data requirements, and the decision you need to make. Work with Sift to identify a useful starting point and how to evaluate it.
Talk to a Sift engineer
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