SupremeTech: Building the Future of Healthcare AI with Agentic AI

Have you ever wondered what agentic AI could do for people’s health? At the intersection of medicine and technology, emerging solutions promise not just smarter systems, but more compassionate care.

AskUnali, in collaboration with SupremeTech, is developing an agentic AI system designed to process vast amounts of medical research, reason through the findings, and provide safe, personalized, science-backed recommendations for patients with chronic illnesses. To explore this journey, we spoke with the co-founder, Gauthier Salavert. He shared the vision behind the product, the challenges of bringing it to life, and how their partnership with SupremeTech is shaping the future of healthcare AI.

Mission and Vision

This mission-driven startup was born from the personal experiences of its founders, two brothers who saw different sides of chronic illness. Gauthier, an entrepreneur based in Germany, understood the challenge from the patient’s perspective. Meanwhile, his brother has witnessed chronic illness from the lens of a medical professional. Together, they empathized with how many patients live with chronic conditions without receiving enough support beyond conventional medicine.

The client aims to elevate wellness and complementary healthcare to the same standards and rigor applied in conventional medicine.

“The worst thing you can say to a patient is not that there’s no treatment,” Gauthier explains. “The worst thing you can say is that you won’t even try to help them.”

Gauthier Salavert

“Until now, complementary care has often been handled informally, but the standard needs to be raised. We live in a unique point of time where there’s an explosion of research papers and discoveries being made, and the rise of LLMs that enable us to scan knowledge at scale. The knowledge base and tools are available to scan the knowledge at scale. We can take…60 million, or so, research papers and parse through them, analyze, then check for relevance and scientific accuracy. This is the first time in history where we can do this.”

Gauthier Salavert

Product Overview

At the center of this mission is an AI chatbot powered by Agentic RAG. Unlike a consumer-facing symptom checker, AskUnali is designed for healthcare institutions and insurers. Through an API, it integrates directly into their platforms, enabling doctors, care teams, or insurance representatives to access safe, science-backed recommendations for chronic conditions.

In practice, a patient might ask, “Do vitamin D gummies help with energy?” Instead of receiving a vague or generic answer, this system returns a contextualized response grounded in science. The response outlines when vitamin D may help, what other nutrients could be relevant, and what sources to consider—all while staying within safe, evidence-based boundaries.

By focusing on institutions rather than direct consumers, our client ensures that the product is both clinically reliable and aligned with the standards required by organizations that carry responsibility for patient safety.

Why they turned to SupremeTech

Gauthier knew that bringing such a product to life required the right partner. He states, “Our bread and butter is R&D and data science, but we needed a software partner to handle development so we could focus on research and business. SupremeTech understood not just the technical side, but the bigger picture.”

Additionally, startups often face business challenges such as resource management and tight timelines. For our client, the key was finding a team that could not only deliver technical expertise, but also adapt as the project evolved. The bottom line: they were looking for a partner who would understand the bigger picture, anticipate challenges, and contribute ideas—not just write code.

By working with SupremeTech as a technology partner, our client was able to accelerate development while maintaining full ownership of the product vision, design, and intellectual property. This clear division lets both companies focus on what they do best—AskUnali on R&D and innovation, SupremeTech on robust and scalable implementation.

SupremeTech’s Contribution

SupremeTech was able to assemble a team quickly and adjust capacity month by month, giving the client the agility a startup needs to keep momentum. This flexibility ensured that development did not slow down, even when priorities shifted.

Gauthier mentions, “SupremeTech was more than just a vendor. The team took true ownership of the project, contributing ideas and improvements rather than simply following instructions”.
By contributing ideas, refining approaches, and aligning with this client’s mission, the collaboration became a true partnership aimed at building a world-class healthcare AI solution.

The team worked together to raise the accuracy of responses to above 97%, while also improving consistency and dependability. In healthcare, where safety and trust are critical, even small improvements to accuracy translate into a stronger foundation for growth.

Through its contributions, SupremeTech helped move this agentic AI MVP closer to production, ensuring the system was functional, safe, reliable, and scalable.

The Challenges that SupremeTech Team Overcame

Building a healthcare product with agentic AI comes with unique technical challenges. The team faced two of the toughest issues early on: ensuring output consistency from the AI and testing the system at scale with large datasets.

Challenge 1: AI Output Consistency

Problem: Random Number Generation (RNG) caused inconsistent outputs, even with the same input and configuration. This made it difficult to guarantee accuracy and reliability in every response.

Quote from SupremeTech’s AI Engineer: “Bringing the application up is not the hard part. The real challenge is keeping the output of GenAI consistent with the requirements, or reaching an acceptable accuracy rate.”

SupremeTech’s Solution: To ensure the stability of output, SupremeTech refined prompts, introduced stricter constraints, and made thoughtful model choices—sometimes opting for older yet more reliable versions instead of the newest releases. A key breakthrough came with LangSmith, a platform from LangChain. SupremeTech used LangSmith to run A/B testing, evaluations, prompt version control, and dataset management. This gave the developers a clear view of how prompts performed across different scenarios. This tool-based approach allowed the team to systematically monitor and improve the AI’s accuracy while reducing randomness in outputs.

Challenge 2: Large Dataset Testing

Problem: Testing with enormous datasets required multiple manual steps, such as cleaning, filtering, and validating the datasets. This was time-consuming and hard to scale as the project grew.

Quote from SupremeTech’s Tester: “For AI projects, the same prompt can generate slightly different answers, and this made it difficult at first to evaluate consistency and quality.”

SupremeTech’s Solution: The team adopted a prompt-as-test-case methodology. Each prompt was treated like a structured test case with defined inputs and expected outputs. Rather than simply logging unclear answers as bugs, the QC process actively refined prompts by adding context, examples, or constraints to better guide the model. This QC-driven prompt engineering shortened the feedback loop and delivered higher-quality prompts to developers.

Another important step was also the use of LangSmith. With its tracing, versioning, and comparison features, SupremeTech was able to track input-output flows, monitor prompt evolution, and measure improvement. By versioning prompts like test cases, the team could compare results before and after changes, quickly spotting where the model improved or failed. This structured approach enabled SupremeTech to handle large volumes of data efficiently and ensure consistency even as the project scaled.

These solutions highlight how SupremeTech’s expertise and experience make it a trusted partner for startups tackling complex agentic AI challenges in sensitive industries like healthcare.

Looking Ahead

According to Gauthier, the most exciting part of this journey isn’t just what has been achieved so far—it’s what’s still ahead. He sees the future of healthcare being shaped by the convergence of technologies that have matured over the past decade. In the innovation aspect, agentic AI plays a central role to reason across vast datasets, integrate information securely, and deliver personalized care at scale.

Beyond the technology, Gauthier also emphasized the importance of having the right partner for the journey, stating, “We feel like we can do anything together. Tech is only part of the journey, but with a strong partner, we can keep growing the product and functionality to make this product the gold standard AI solution in this space.”

As we moves toward production, the company is positioned with confidence; with SupremeTech as a long-term partner, the team is equipped to keep innovating.

Conclusion

This case study shows how vision and technology can come together to enhance healthcare. By partnering with SupremeTech, the team has transformed complex agentic AI challenges into a reliable foundation for growth. Through this collaboration, SupremeTech demonstrates its role not only as a technology provider, but as a committed partner bringing bold ideas to life.

👉 If you’re looking for a technical provider to help build and scale your AI product while retaining full ownership of your vision and IP, SupremeTech is ready to help.