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Arttac Solutions is a health-tech company specializing in AI-powered diagnostics designed to make disease detection faster, more reliable, and widely accessible. Their mission is to use intelligent systems to support medical professionals with tools that improve clinical accuracy and efficiency.
One such focus is Small Intestinal Bacterial Overgrowth (SIBO), a condition often underdiagnosed due to the complexity and time-consuming nature of traditional testing methods. By rethinking the diagnostic process, Arttac sought to combine AI, data-driven insights, and automation to make SIBO detection more accurate and scalable.
We partnered with Arttac to design and deliver an AI-driven diagnostic platform that brings this vision to life, transforming how SIBO testing is performed and interpreted.
The challenge was multi-layered. Training an AI model with limited initial datasets required precision to avoid compromising clinical accuracy. At the same time, the platform had to be scalable enough to support multiple test types as adoption grew, while also generating structured, professional-grade diagnostic reports that patients and clinicians could trust.
Arttac also required the system to learn continuously, improving with every test kit processed. This meant building an auto-training pipeline capable of refining model accuracy in real time while maintaining rigorous validation standards expected of healthcare tools.
At the core of the platform is a custom machine learning pipeline engineered to predict SIBO likelihood from patient test results. To support continuous learning, we built an auto-training mechanism that refines performance as new data flows in, ensuring accuracy improves over time. Rigorous validation protocols were applied at every stage to guarantee predictions met healthcare-grade standards.
For patients and clinicians, trust and usability were non-negotiable. We designed structured diagnostic reports that communicate results clearly, balancing medical rigor with readability. By applying human-centered design principles, we ensured the platform could be adopted seamlessly into clinical workflows while remaining intuitive for non-technical users.
Scalability was built into the foundation. The platform’s cloud-native architecture supports multiple diagnostic test types beyond SIBO and is equipped with a robust codebase and testing framework to maintain reliability as adoption expands.
At the core of the platform is a custom machine learning pipeline engineered to predict SIBO likelihood from patient test results. To support continuous learning, we built an auto-training mechanism that refines performance as new data flows in, ensuring accuracy improves over time. Rigorous validation protocols were applied at every stage to guarantee predictions met healthcare-grade standards.
For patients and clinicians, trust and usability were non-negotiable. We designed structured diagnostic reports that communicate results clearly, balancing medical rigor with readability. By applying human-centered design principles, we ensured the platform could be adopted seamlessly into clinical workflows while remaining intuitive for non-technical users.
Scalability was built into the foundation. The platform’s cloud-native architecture supports multiple diagnostic test types beyond SIBO and is equipped with a robust codebase and testing framework to maintain reliability as adoption expands.
The AI-powered platform has already begun to accelerate SIBO diagnosis, giving clinicians faster and more reliable insights compared to traditional methods. Patients benefit from clearer, structured results, while providers gain confidence in using AI-assisted tools to guide care.
Through its auto-training feature, the system continuously improves with each new dataset, setting a new benchmark for adaptive diagnostic tools. The platform also provides a scalable foundation for future growth, ready to incorporate additional test types and expand into broader medical diagnostics.
By combining AI intelligence, user-centered design, and scalable engineering, we helped Arttac Solutions move from concept to deployment in just six months, and into a second phase of product evolution soon after. Together, we demonstrated how AI can transform diagnostics for niche but impactful conditions, positioning Arttac as a leader in the next wave of intelligent healthcare innovation.
The AI-powered platform has already begun to accelerate SIBO diagnosis, giving clinicians faster and more reliable insights compared to traditional methods. Patients benefit from clearer, structured results, while providers gain confidence in using AI-assisted tools to guide care.
Through its auto-training feature, the system continuously improves with each new dataset, setting a new benchmark for adaptive diagnostic tools. The platform also provides a scalable foundation for future growth, ready to incorporate additional test types and expand into broader medical diagnostics.
By combining AI intelligence, user-centered design, and scalable engineering, we helped Arttac Solutions move from concept to deployment in just six months, and into a second phase of product evolution soon after. Together, we demonstrated how AI can transform diagnostics for niche but impactful conditions, positioning Arttac as a leader in the next wave of intelligent healthcare innovation.