Cradle

About Cradle

Cradle is a cutting-edge platform designed for biotech professionals seeking to streamline protein design. Utilizing advanced machine learning, it generates optimized protein variants efficiently, predicting performance outcomes to reduce lab surprises. Cradle empowers teams to enhance their projects and accelerate results within their existing workflows.

Cradle offers a straightforward annual subscription model with a single flat fee ensuring users retain full ownership of their intellectual property. There are no hidden royalty fees, making it an accessible option for biotech teams aiming to expedite their projects while maximizing resources and efficiency.

Cradle's user interface is intuitive and streamlined, allowing users to navigate seamlessly through its features. Designed for ease of interaction, the layout prioritizes clarity and efficiency, ensuring users can quickly set up assays, generate sequences, and manage lab results without unnecessary complexities.

How Cradle works

To get started with Cradle, users simply set up desired assays and objectives, guiding the platform on their measurement goals. Next, they generate optimized sequences using Cradle's advanced machine learning capabilities. Users then test these sequences in the lab and can easily import results to refine their projects continuously, ensuring productivity and precision throughout the process.

Key Features for Cradle

Machine Learning-Driven Protein Design

Cradle’s unique machine learning-driven protein design feature enables users to create improved protein variants efficiently. By predicting performance outcomes, Cradle reduces the guesswork involved in protein engineering, allowing scientists to focus on experimentation and innovation rather than manual analysis.

Multi-Property Optimization

Cradle offers multi-property optimization, allowing users to address various properties and tasks in a single round. This innovative feature saves time and enhances model learning, making it easier for users to achieve their project goals while maximizing experimental efficiency and effectiveness.

Data Privacy and Ownership

Cradle emphasizes data privacy and ownership. Users have complete control over their sequences and experimental results, ensuring that their data remains exclusive and secure. This commitment to private access reinforces trust and allows researchers to innovate without concerns about external data use.