What we do
Converge Lab is a venture builder designed to bridge the worlds of science and entrepreneurship.
We exist to help researchers turn their discoveries into real-world solutions – responsibly, strategically, and globally.
We co-found startups based on breakthrough scientific research.
Our team provides end-to-end support: technical validation, regulatory alignment, legal structuring, business modeling, and investor readiness.
A model designed for those who think ahead
We support researchers and investors who believe in the transformative power of science. Our model combines technical validation, strategic structuring, and global ecosystem connections to turn research into impact.
Co-founders in practice
We work side by side with scientific teams — from thesis to fully structured company.
Technical and regulatory validation
We ensure each project is ready to move forward with strength and compliance.
International network
We connect Brazilian science with global partners, investors, and markets.
A model designed for those who think ahead
We support researchers and investors who believe in the transformative power of science. Our model combines technical validation, strategic structuring, and global ecosystem connections to turn research into impact.
Co-founders in practice
We work side by side with scientific teams — from thesis to fully structured company.
Technical and regulatory validation
We ensure each project is ready to move forward with strength and compliance.
International network
We connect Brazilian science with global partners, investors, and markets.
Researchers
Turn your research into a deeptech with technical, legal, and strategic support.
Investors
Invest with lower risk in validated solutions with high potential for impact and return.
Real Cases of Deep Tech Innovation
InsilicAll
Discovery and optimization of materials for energy efficiency: CSP allows for the prediction and design of new materials for thermal dissipation, energy storage, insulators, and semiconductors that consume less energy or can withstand higher loads without increasing energy consumption. Through predictive modeling, InsiliAll makes it possible to search for alternatives to hard-to-obtain metals (such as cobalt, lithium, or rare earth elements), designing more abundant and recyclable compounds without sacrificing performance. CSP enables the evaluation of the stability, recyclability, and toxicity of new materials during the design phase, prioritizing synthesis routes with a lower environmental footprint.
Polymorph ID
Polymorph ID is a cutting-edge project, acting in pharmaceutical development to identify and characterize different crystal forms (polymorphs) of a compound. Each polymorph can have distinct physical and chemical properties, such as solubility, stability, and bioavailability, which are critical for drug efficacy and manufacturability. By accurately detecting and analyzing these forms, Polymorph ID supports the development of safer, more effective, and patentable medications.
InsilicoAI
InsilicoAI’s cocrystal project leverages artificial intelligence to design and predict cocrystals—crystalline structures formed by two or more components, typically an active pharmaceutical ingredient (API) and a coformer. These cocrystals can enhance key drug properties such as solubility, stability, and bioavailability without altering the molecule’s pharmacological profile. By integrating advanced materials science with AI-driven modeling, InsilicoAI accelerates the discovery and optimization of cocrystals, reducing trial-and-error in the lab and enabling more efficient pharmaceutical innovation.
Supported by leading institutions
