Problem

Protein engineering is slowed by an iterative wet-lab process: biologists must generate protein variants, test them, learn from the results, and repeat. That experimentation creates time, cost, and development-cycle risk, particularly when teams are trying to improve several properties at once. Cradle’s central use case is shortening this cycle for the discovery and optimization of therapeutic and industrial proteins, including enzymes, antibodies, and other bio-based products.

Product / Service

Cradle provides a business-to-business machine-learning software platform for protein engineering. Its prediction algorithms and AI design recommendations help scientists generate protein candidates and improve their properties, while incorporating the customer’s own experimental data to guide subsequent designs. The platform supports multiple protein modalities and applications, including antibodies, enzymes, peptides, vaccines, and therapeutic proteins.

The benefit is better protein candidates with fewer experimental rounds, accelerating the development of therapeutics and bio-based products. Cradle also emphasizes customer ownership of intellectual property and the privacy and security of users’ sequences and data, which are important requirements for pharmaceutical and industrial customers.

Market

Cradle competes in AI-enabled protein engineering and computational protein-design software, serving biopharma and industrial-biotechnology customers across pharmaceuticals, chemicals, food, and agriculture. The available evidence indicates that Cradle has competitors in this category, but does not name specific rival companies, so a reliable competitor-by-competitor comparison cannot be made from the supplied research.

Cradle was founded in 2021 and appears to be a commercial, rather than merely pre-revenue, company: it has reported serving six of the top 25 pharmaceutical leaders and raised a $73 million Series B, bringing total funding to more than $100 million. Third-party sources provide revenue estimates, but they conflict and are explicitly non-audited estimates, so the company’s actual revenue is not established by the available evidence.