Cradle

What is Cradle?

Cradle is an advanced AI-assisted protein engineering platform designed for biologists, biopharma researchers, and industrial R&D teams. By connecting protein design and optimization into a unified workflow, Cradle allows scientists to train custom machine learning models on their own assay data and iteratively engineer proteins with multi-property profiles.

By leveraging evolutionary context and active learning, Cradle enables simultaneous multi-objective optimization (such as catalytic activity, stability, yield, and solubility) starting from as few as 96 variants. It helps teams cut discovery times significantly, de-risk pipelines, and generate performant candidates for antibodies, enzymes, vaccines, and peptides.

• Platform Focus: AI protein engineering, multi-objective protein design, directed evolution acceleration, and custom ML assay learning
• Developer / Entity: Cradle Bio
• Launch Year: AI-Assisted Protein Design Platform

Use Cases:

• Accelerating antibody discovery, affinity maturation, and early liability mitigation (thermostability, expression, and developability)
• Optimizing industrial enzymes for heightened catalytic activity, yield, and resistance to harsh operational conditions
• Designing and stabilizing viral antigens and vaccine candidates to maintain structural integrity outside the lab
• Engineering specialized therapeutic peptides under strict sequence and property constraints
• Forecasting round hit rates and scoring candidate variant plates before committing wet-lab budget

Technology:

• Customizable machine learning models trained iteratively on proprietary experimental assay data and fitness landscapes
• Multi-objective parallel optimization engine handling trade-offs across competing targets (e.g., activity vs. expression)
• Flexible deployment via user-friendly web interfaces and programmatic APIs for computational teams
• Enterprise-grade security infrastructure (ISO 27001 and SOC 2 Type II certified with data isolation)

Target Users:

• Biologists and wet-lab bench scientists conducting protein expression and screening assays
• Computational biologists and bioinformaticians integrating custom APIs into R&D pipelines
• Biopharma enterprises, agricultural biotech innovators, and industrial enzyme developers

Corporate Entity: Operates as Cradle Bio / cradle.bio

Key features of Cradle

Cradle's key features are

• Iterative Active Learning: Trains project-specific AI models on your wet-lab assay data to map individual protein fitness landscapes.
• Simultaneous Multi-Property Optimization: Optimizes all target specifications (activity, stability, yield, developability) in parallel across design rounds.
• Round Forecasting & Scoring: Predicts hit rates, score distributions, and remaining headroom on candidate plates before committing lab spend.
• Assay Agnostic Ingestion: Ingests diverse experimental data formats including NGS from FACS screening, ELISAs, and chromatography readouts.
• Precision Mutation Control: Direct models to introduce mutations freely or restrict changes to specific active sites, loops, or antibody CDRs.
• Actionable Analytics & Reports: Clear data visualizations and mutation comparisons to guide the next round of laboratory experiments.

Cradle Pricing

Cradle operates on a commercial software license model tailored for biotechnology companies and research institutes.

Enterprise & Team Licenses:

• Custom enterprise software licensing providing platform access, API integration, and private isolated data environments (No royalties or milestone fees)

Who is using Cradle?

Cradle is trusted by global biopharma leaders and bio-based innovators, including

• Global Biopharma Leaders: Bayer (Drug Discovery Sciences), Novonesis, and top-50 pharmaceutical R&D teams
• Agricultural & Industrial Biotech: Corteva Catalyst and sustainable material enterprises
• Academic & Research Groups: University labs engineering novel binders and enzymes

Best Cradle Alternatives

Some of the strongest AI protein engineering and design alternatives include

• Profluent
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• EvolutionaryScale (ESM)
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• Ginkgo Bioworks
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• AlphaFold (Google DeepMind)
• Absci
• Insempra

Pros and Cons of Cradle

Pros

• Drastically cuts R&D turnaround times and wet-lab iteration cycles (up to 2–12x faster)
• Simultaneous multi-objective optimization prevents gains in one property from degrading another
• User-friendly interface allows bench scientists to harness machine learning without deep coding experience
• Privacy-first architecture ensures client assay data is strictly used for proprietary model training

Cons

• Requires wet-lab assay data or a starting sequence to power effective active-learning cycles
• Enterprise pricing is gated behind custom sales consultations rather than self-serve public tiers
• Complex biological targets may still require iterative physical screening and empirical validation

Why Choose Cradle?

Cradle is an essential platform for biotechnology and biopharma teams looking to transcend traditional trial-and-error protein engineering by combining generative AI, active learning, and multi-objective optimization into an intuitive workspace.

• Accelerates protein discovery timelines by learning directly from your assay data
• Handles complex multi-property profiles for antibodies, enzymes, and peptides
• Provides seamless collaboration tools alongside robust enterprise security (SOC 2 Type II)
• Offers transparent forecasting to optimize wet-lab spending and de-risk pipelines

Cradle vs. Competitors

The main difference between Cradle, EvolutionaryScale, Profluent, and AlphaFold is that Cradle provides an interactive, scientist-centric software platform focused on active learning and multi-objective optimization from proprietary user assays, whereas AlphaFold predicts static 3D structures, and models like ESM or Profluent focus primarily on zero-shot foundational generative sequence design. Cradle stands out for its end-to-end directed evolution loop.

How do we rate Cradle?

Cradle Review

Cradle is a phenomenal platform that bridges the gap between machine learning and wet-lab protein engineering. By providing an active-learning workspace where scientists can optimize multiple properties simultaneously and forecast plate hit rates, it removes much of the guesswork from directed evolution. Backed by major pharma partners like Bayer, Cradle represents the cutting edge of AI-assisted biotechnology.

Conclusion

Cradle is a leading AI protein engineering software platform that empowers scientists to build better proteins faster. By turning assay data into custom generative models, it streamlines the design and optimization of antibodies, enzymes, and therapeutics with unprecedented precision.