An AI co-pilot for scientists designing new biomaterials

This article is a part of Startup Spotlight, a series that features young, up-and-coming startups.

Image credit: Timmy Loen

Zi Ying Tan spent years in wet labs manually testing molecules one at a time. Each cycle took weeks, with most effort wasted. She saw a gap between AI’s potential and how biology R&D still operated.

This led to M3triq, a startup building an AI co-pilot to automate this painstaking work. M3triq recently won the Agentic Track at a global hackathon hosted at Nvidia’s headquarters.

😟 Problem

Modern biology research and development runs on complex and fragile computational workflows. Most lab-based science teams lack the resources to build or maintain them.

Teams must either hire scarce bioinformatics specialists or manually connect many different software tools. This process is slow, expensive, and difficult to reproduce.

💡 Solution

M3triq provides an agentic AI layer that orchestrates entire bioinformatics workflows. It gives scientists a single interface to move from a protein target to ranked candidates. The platform automates several key processes:

• Simulating protein-ligand interactions.
• Prototyping new ligands and media components in silico.
• Ranking candidates for stability, scalability, and safety.
• Surfacing options compatible with GRAS, FDA, or EFSA standards.

Image credit: Timmy Loen

📊 Market size

M3triq targets a subset of the global biotech market. This includes roughly 2,000-3,000 companies in biomaterials, therapeutics, and bioprocessing that need but lack in-house computational tools.

Serving 1,000 of these companies with contracts of US$25,00–$50,000 annually represents a US$25 –$50 million annual recurring revenue opportunity.

🤝 Team

• Zi Ying Tan. Co-founder and CEO. PhD in stem cell biology with industry experience in cultivated meat media and cell-based biomaterials. She defines the platform’s scientific workflows and constraints.
• Khai Jien Kong. Co-founder. PhD in Synthetic Biology from University College London with experience in immune engineering and deep-tech ventures. He leads the platform’s technical development.

🚀 Traction

• Engaged with 5–7 cultivated meat companies under licensing and royalty-style agreements.
• Launched a paid pilot with an enterprise-scale ingredient company to test AI-designed candidates.
• Won the Agentic Track at the Hackathon Global Sprint at Nvidia’s headquarters, selected from over 115 applicants.

🏆 Competition

💰 Financials