AI-Powered Urine Test and Analysis

The problem

People notice symptoms at home long before they can see a doctor. At-home urine strips already exist, but reading them by eye is error-prone, the results are easy to misjudge, and there is no clear next step once a strip changes colour. A UK health-tech client wanted to close that gap: let someone test at home, get a reliable reading in seconds, understand what it means, and reach a clinician when the result calls for it. The work had to handle sensitive health data under GDPR from the first line of code.

The solution

We built a mobile app, branded PURI, that turns a paper strip into a structured medical reading and a clear recommendation. The build covered five areas:

• AI strip reading and risk scoring: a machine learning model reads the strip from the phone camera, normalises for lighting and device, and scores risk for conditions such as urinary tract infections and early kidney issues. The model accounts for variation in test conditions, which is where most false readings come from.
• Data privacy by design: end-to-end encryption and GDPR-compliant storage, so sensitive results stay protected and the client stays compliant from day one.
• Telemedicine handoff: when a result needs follow-up, the app connects the user to a clinician for remote advice, so a worrying strip leads to real guidance instead of a dead end.
• Guided testing and education: step-by-step result entry, a built-in test library, quizzes, and progress tracking that help users test correctly and read their own history with confidence.
• Wide device support and multiple languages: tuned to run on older phones and translated for several languages, so the app reaches people who are usually left out.

The results

Compared with the client's earlier in-house plan and manual strip reading, the delivered app moved the numbers that mattered:

• 30% fewer false positives from AI strip reading versus reading colours by eye.
• 25% higher patient retention among users who engaged with telemedicine and the in-app education.
• 30% shorter development cycle by reusing proven components instead of building every part from scratch.
• 40% lower cost than building the same product with an in-house team.
• Fewer repeat tests, because a complete result history is kept on the device.

How it works

The user dips a standard strip, photographs it in the app, and waits about sixty seconds. The model reads each pad, corrects for lighting, and returns a result with a plain-language risk score and a recommended next step. Results are stored on the device and can be shared with a clinician through the telemedicine feature. Because the reading is consistent every time, the user gets the same standard whether they test at 8am or midnight.

Compliance and trust

Health data carries real obligations, so the app was built to GDPR from the start, not retrofitted later. Data is encrypted end to end, storage follows GDPR rules, and the telemedicine handoff keeps a clinician in the loop for anything clinical. That mix of secure handling and human follow-up is what gave users the confidence to share sensitive results.

FAQ

How accurate is the AI reading compared with reading a strip by eye?

In this project, AI reading cut false positives by 30% against manual colour matching, mainly by correcting for lighting and device differences that trip up the human eye.

Does the app replace a doctor?

No. It gives a fast reading and a clear recommendation, then connects the user to a clinician through telemedicine when a result needs professional follow-up.

What happens to the health data?

Results are encrypted end to end and stored under GDPR rules. A full history stays available to the user, which also reduces repeat testing.

Can it run on an older phone?

Yes. The app was tuned for older devices and translated into several languages so it reaches a wider group of users.

Conclusion

PURI shows what at-home diagnostics can be when the reading is reliable and the next step is clear. AI scoring, secure data handling, and a direct line to a clinician turn a paper strip into a tool people actually trust and keep using. For the client, it meant fewer false alarms, better retention, and a product delivered faster and at lower cost than an in-house build. This is the kind of compliant, outcome-focused healthcare software Life Value builds for teams that need to move quickly without cutting corners.