When you attend Web Summit 2025, you expect to see the future.
Amidst the noise of thousands of startups and investors in Lisbon, one encounter stood out to me. I had the pleasure of meeting the team behind ThinkerMesh, a Porto-based engineering firm that is quietly rewriting the rules of diagnostics.
If you work in HealthTech or MedTech, you know the pain points of the traditional laboratory environment: rigid, expensive legacy software that barely talks to other systems, let alone integrates modern AI. That’s exactly what ThinkerMesh is solving.
🧪 The Problem: Labs Are Stuck in the Past
Pathology and diagnostic labs are under immense pressure to increase throughput and accuracy, but their digital backbone—the Laboratory Information System (LIS)—is often their biggest bottleneck.
Existing solutions are:
- Costly and Rigid: They don’t adapt well to new workflows or smaller markets.
- Fragmented: Data silos prevent effective use of AI and automation.
- Slow to Innovate: Integrating new AI models for things like slide analysis is a logistical nightmare.
💡 The Solution: A Modular, AI-First Ecosystem
ThinkerMesh isn’t just building another LIS; they are building a “mesh” of intelligent modules powered by a robust AI marketplace.
Their approach is grounded in “industry-embedded design”. By co-developing their platform with IMP Diagnostics, they are validating their workflows in a real-world pathology environment from day one.
Here is what makes their AI-Powered Laboratory Information System unique:
- Modular Architecture: Labs can “tinker deliberately and prototype quickly,” using only the modules they need.
- AI Marketplace: A curated space for geo-controlled, regulation-aware AI models (like WSI segmentation and cell counting) that labs can monetize and deploy safely.
- Digitization & Auto-QC: They automate quality control and digitize workflows (OCR) to reduce errors and optimize staff time.
👥 Meet the Architects
The vision comes from a team that bridges the gap between deep tech and clinical reality:
- Ricardo Pimentel: A seasoned engineering leader (formerly Head of AI Engineering at Rystad Energy).
- Usman Yasin: A Solution Architect and Big Data specialist ensuring the platform scales securely.
🤝 Synergies: How YOUR R&D Can Accelerate the Mesh
At YOUR R&D, we specialize in providing the private engineering engines that power ambitious HealthTech roadmaps.
ThinkerMesh is entering a critical phase: Phase 1 (Discover & Build) and moving toward Phase 2 (clinical validation). This requires rapid scaling of engineering talent to build device integrations and refine the marketplace infrastructure without slowing down core R&D.
This is where we align.
While ThinkerMesh focuses on the clinical strategy and AI model governance, YOUR R&D can supply the scalable, mixed-discipline engineering teams needed to build out the underlying modular “mesh” and web interfaces. We love partners who believe in the philosophy of “think slow, act fast”—validating deeply before scaling rapidly.
🔮
The future of diagnostics isn’t just about better microscopes; it’s about better software. ThinkerMesh is paving the way for a lab environment that is collaborative, automated, and intelligent.
We are excited to watch their journey from Porto to the global stage.
What do you think is the biggest barrier to AI adoption in clinical labs today? Let’s discuss in the comments!
🔗 Explore ThinkerMesh: Visit Website
#HealthTech #MedTech #AI #LaboratoryInformationSystem #SoftwareDevelopment #Innovation #WebSummit2025
