Protein engineering without the guesswork Design improved variants of your target protein sequence with just a few clicks — and some machine learning.
Bring lab data or start fresh Get started by importing assay data from an ongoing project – or start fresh from just a single starting sequence.
No surprises in the lab Each generated sequence comes with a predicted performance score. Less exciting for some, more productive for everyone.
AI-driven protein engineering platform that accelerates candidate generation and optimization, achieving results 2-12x faster than traditional methods.
Supports simultaneous multi-property optimization, allowing for balanced improvements across various protein characteristics in a single experimental round.
Integrated wet lab validation ensures continuous improvement of AI models based on real experimental data, enhancing prediction accuracy.
Provides a unified workflow for sequence generation and property prediction, facilitating efficient optimization of multiple enzymes and proteins.
Offers enterprise-grade security and privacy, ensuring that user data and intellectual property remain confidential and protected.
Accelerating the discovery and optimization of therapeutic antibodies by integrating AI into existing R&D workflows, as demonstrated in the collaboration between Bayer and Cradle.
Enhancing the thermostability of vaccine candidates, such as a chimeric Staphylococcus aureus vaccine, achieving significant improvements in a single experimental round compared to traditional methods.
Utilizing AI to produce vaccine adjuvants, like QS-21, through precision fermentation, thereby reducing reliance on natural resources and addressing sustainability concerns.
Implementing machine learning to optimize multiple properties of proteins simultaneously, allowing for faster and more efficient development cycles in biopharma and industrial bio sectors.
Facilitating the management of experimental data and workflows through a unified platform, enabling scientists to track progress and improve candidate selection based on real-time feedback.
Accelerates protein engineering processes, achieving development timelines that are 2-12 times faster than traditional methods.
Enables simultaneous optimization of multiple protein properties, reducing the number of experimental rounds needed to reach desired outcomes.
Utilizes AI to learn from unique experimental data, improving the accuracy of predictions and enhancing the efficiency of the design process.
Provides a secure platform where users retain full ownership of their data and intellectual property, ensuring privacy and compliance.
Facilitates collaboration across teams by maintaining a unified workspace, allowing for shared data, models, and learning loops to compound results.
Standard Plan: Annual license based on the number of active projects for organizations running one to several programs.
Enterprise Plan: Flexible scaling for organizations with multiple projects, allowing deployment across programs and divisions.
Academic Plan: Tailored for not-for-profit research, with limited availability and requires an application to join.
Included in All Licenses: Private workspace, full ownership of sequence IP, unlimited users, data upload and storage, and expert technical support with no hidden fees.
No Royalty or Milestone Fees: Simple annual software license without complicated royalty deals or milestone payments.
