Cradle

Cradle is a web-based platform AImed at protein engineers and synthetic biology teams who want to shorten the design-build-test cycle. Rather than treating machine learning as a one-off prediction step, it wraps predictive algorithms and design recommendations into an iterative workflow that connects computational candidate design with real laboratory results.

What it does

The platform lets researchers visualize, analyze, and rank candidate protein designs in a single workspace, then generate new proposals based on what the models have learned. The core IDEa is that each round of wet-lab testing feeds results back into the system, allowing the underlying models to be retrained and refined so subsequent rounds produce better candidates.

Key capabilities

• Predictive scoring: estimate the potential of protein variants before committing lab resources.
• Design suggestions: generate high-quality candidate sequences or variants with minimal manual configuration, reportedly with a single CLIck.
• Iterative model improvement: train custom models on your own experimental outcomes so recommendations sharpen over successive rounds.
• Low-throughput compatibility: the company states projects can progress using Standard 96-well plate assays, so teams without high-throughput screening are not excluded.
• Centralized analysis: compare, visualize, and prioritize candidates in one place instead of stitching together separate tools.

Who it is for

Cradle is intended for discovery and protein engineering groups in biotech and academic labs, particularly teams working on enzyme optimization, binder design, or other directed-evolution style campaigns. It is likely most valuable to organizations that already run regular wet-lab rounds but lack in-house Machine Learning infrastructure or the data science staff to maintain custom predictive models.

How to get started

Prospective users typically begin by contACTing the company through its website to discuss a project or request a dEMO. New teams should expect an onboarding conversation covering assay setup, data formats, and how results will be returned to the platform between rounds. Because the service depends on experimental feedback, planning the first assay round carefully is worthwhile.

Pricing and access caveat

Specific pricing is not publicly documented in a standard tier list and may vary by project scope, usage volume, and commercial terms, so it should be confirmed directly with Cradle. trial availability and academic arrangements may also change over time. The platform is delivered through a web browser, and the languages, regional availability, and feature set may differ from what is described here as the product evolves.