Side-by-side comparison of AI visibility scores, market position, and capabilities
Cradle provides an AI platform for protein engineering that accelerates the design of improved enzymes, antibodies, and other biologics for industrial and therapeutic use.
Cradle Bio is an AI protein engineering company founded in 2021 in Amsterdam, having raised $73M to build an AI-powered protein design platform. The platform combines generative AI with wet-lab experimentation to accelerate the iterative process of engineering proteins with improved stability, activity, and manufacturability. Cradle's technology enables researchers to design thousands of protein variants computationally and prioritize those most likely to succeed in laboratory validation, compressing protein engineering timelines from years to months. The company serves both industrial biotechnology customers engineering enzymes for biomanufacturing and pharmaceutical companies developing next-generation antibody therapeutics. Cradle partners with contract research organizations and biopharmaceutical companies to integrate AI-assisted protein design into existing discovery workflows. The company has been recognized as a leader in the European deep tech ecosystem and positions protein engineering AI as enabling a new era of designed biologics for medicine and sustainable manufacturing.
Pioneering organ-on-chip platform installed in 150+ labs including 17 of the top 25 biopharma companies; launched AVA™ high-throughput 96-chip system in 2025 and holds the only FDA ISTAND-accepted DILI Organ-Chip.
Emulate, Inc. is a Boston-based biotechnology company that designs, manufactures, and commercializes Organ-Chip technology — micro-engineered devices lined with living human cells that replicate the microstructure and function of human organs. Founded in 2013 as a spin-out from the Wyss Institute at Harvard University, Emulate's chips model the liver, intestine, lung, kidney, brain, and other organ systems with a fidelity that animal models and traditional cell culture cannot match. The technology was originally developed to reduce drug development attrition rates caused by poor translation from animal studies to human clinical outcomes.
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