Engineering for patient safety now requires a mindset built for change. The regulatory landscape has shifted away from the concept of a static software lifecycle toward a lifecycle of continuous improvement and adaptation. With the FDA's focus on Predetermined Change Control Plans (PCCP), your competitive advantage is no longer just the hardware you ship - it is an architecture that can update and retrain safely while in clinical use. We partner with you to build these resilient systems, making sure your software remains compliant and reliable as it evolves.
Updating an AI model often breaks traditional validation. Proving safety on your hardware should not take your team months of manual testing. We build automated Hardware-in-the-Loop testing into your daily workflow. This gives you mathematical proof that your models work perfectly on your specific microcontrollers every day, not just the day you submit your documentation.
New regulations require you to explain why an AI made a specific decision. However, most wearable or handheld devices lack the memory or battery to run a secondary model just for explanations. We architect lightweight, sparse systems that provide the clarity regulators need without draining the battery or forcing you to use a more expensive processor.
A hospital network is an unpredictable environment. A sudden spike in network traffic should never interfere with a critical therapy loop. We use physical memory protection to keep communication stacks completely separate from core therapy functions. This makes sure your safety-critical code never has to compete for resources with the Wi-Fi chip.
Documentation often feels like a chore engineers do at the very end of a project. That is a primary cause of audit delays. We build traceability into the code from the start. Using CI/CD pipelines, we link every requirement to a test case automatically. By the time an audit begins, the paper trail is already finished because it was a byproduct of the engineering itself.
A medical device is a ten-year commitment. As new threats emerge, patching a fleet of active devices without the risk of breaking them is a significant operational fear. We build secure bootloaders and update paths that are atomic. If an update fails for any reason, the device stays on the last safe version. This makes sure a patient is never left with a non-functioning device.
Once a device is in clinical use, real-world data can cause performance to shift, leading to model drift. Most teams lack a way to monitor this without violating patient privacy. We design edge-monitoring tools that detect these shifts in real-time. This allows you to trigger a retrain or alert the user before the device falls out of its safety envelope, keeping your performance high and your risk low.