How We Implemented an AI Module in a Healthcare Project: The TalkHealth.ai Experience
In healthcare, interpreting lab results correctly isn’t just a matter of accuracy — it’s a matter of trust and clarity. That’s why TalkHealth.ai partnered with Cubex to build a platform that could help users better understand their health data, without losing precision.
What We Built
We developed a web application that:
- uses GPT-4 to analyze and interpret medical test results
- provides simple, non-technical explanations for both patients and doctors
- ensures secure data processing, hosted on AWS
- is built with a modern tech stack: React.js, TypeScript, Nest.js
Why It Works
- AI as an enhancement, not a replacement GPT-4 doesn’t diagnose — it helps interpret results in a way that’s understandable and actionable.
- User-first design In stressful moments, clarity matters. We built an interface that’s intuitive, clean, and responsive.
- Technical stability The app was designed for scale, performance, and compliance with healthcare-grade standards.
Security & Compliance
The solution was developed to meet HIPAA requirements, including:
- end-to-end data encryption
- detailed activity logging
- full adherence to privacy and security best practices
Key Takeaways from This AI Integration
- AI modules should rely on validated, structured medical data
- Explanations must be transparent and accessible to non-technical users
- Your team must combine tech expertise with a clear understanding of the medical context
Planning to Integrate AI into Your Healthcare Product?
At Cubex, we don’t just write code — we build solutions that help healthcare startups scale and deliver value.
Let’s talk if you’re looking for a tech team that can think strategically, build securely, and deliver real impact.
Contact Us
Please contact us for any further information
