Cradle

About Cradle

Cradle is revolutionizing protein engineering by harnessing machine learning to create optimized protein sequences. Targeting biotech teams, it simplifies the design process, enabling users to generate, test, and analyze variants seamlessly. By predicting performance scores, Cradle helps users accelerate projects and overcome research challenges effectively.

Cradle features a flat annual fee subscription model, ensuring transparent pricing without hidden costs. Subscribers gain access to all tools for protein design and optimization. With this approach, users can focus on projects without worrying about royalties, making Cradle a cost-effective solution in biotech innovation.

Cradle offers an intuitive user interface designed for seamless navigation through protein design workflows. Its layout facilitates easy access to features like data import and sequence generation, tailored for scientists. With user-friendly tools and clear visual aids, Cradle enhances productivity and ensures a smooth user experience.

How Cradle works

To use Cradle, users start by setting up assays and defining objectives based on their projects. They input existing assay data or enter a single starting protein sequence to generate optimized variants. The platform uses machine learning to predict performance scores for each sequence, allowing users to test in labs and import results efficiently. This iterative process continually refines the outcomes, making it straightforward for users to achieve optimal results while retaining control over their data and sequences.

Key Features for Cradle

Machine Learning-Driven Optimization

Cradle's core functionality lies in its machine learning-driven optimization, allowing users to generate improved protein variants with ease. By predicting performance scores for each design, Cradle enhances experimental accuracy and efficiency, enabling biotech teams to achieve groundbreaking results faster and more effectively.

Multi-Property Optimization

A standout feature of Cradle is its ability to handle multi-property optimization in a single round. This unique capability allows users to optimize various characteristics of proteins simultaneously, significantly improving research timelines and outcomes by leveraging comprehensive data and advanced machine learning techniques.

Data Security and Ownership

Cradle prioritizes user privacy with robust data security measures ensuring sequences and results remain confidential. Users retain complete ownership of their intellectual property, allowing them to innovate freely. This commitment to privacy and security fosters trust and confidence among users in the biotech field.