Cradle Bio
ML-guided protein engineering platform for multi-property optimization.
Cradle is a top pick for enterprise pharma and industrial bio teams needing secure, multi-property protein optimization with ML-guided campaigns. Its privacy-first design and wet-lab validation add real credibility. However, lack of transparent pricing limits appeal for smaller labs.
Verified 2d ago · liveness 60/100 · cite: rightaichoice.com/tools/cradle-bio
- Biopharma R&D teams engineering therapeutic antibodies, peptides, and vaccines with strict multi-property constraints
- Industrial bio companies optimizing enzymes for catalytic conversions under challenging conditions
- Teams needing to accelerate protein engineering while maintaining IP privacy and enterprise security
- Enterprises requiring SOC 2 compliant, secure AI with SSO and dedicated support for large-scale programs
- Academic labs or startups with limited budgets, as Cradle is enterprise-priced and lacks transparent pricing
- Teams preferring open-source or fully customizable AI models over a managed platform
- Projects where only a single property matters and high throughput is not needed
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Skip Cradle if you cannot commit to providing your own experimental data, need a free or low-cost tool, or require transparent, self-serve pricing.
Pricing is not publicly listed, so you'll need to contact sales for a quote, which may include minimum commitments and subscription fees.
Cradle is enterprise-priced and suited for large biopharma and industrial bio teams with dedicated budgets. It is more expensive than open-source or academic tools but offers secure, private, multi-property optimization that cheaper alternatives may lack.
In short
Cradle Bio — ML-guided protein engineering platform for multi-property optimization. Best for Biopharma R&D teams engineering therapeutic antibodies, peptides, and vaccines with strict multi-property constraints, Industrial bio companies optimizing enzymes for catalytic conversions under challenging conditions, Teams needing to accelerate protein engineering while maintaining IP privacy and enterprise security. Contact Sales pricing.
What's new in Cradle Bio
Checked 2 days agoAcross the latest 5 updates: 2 feature updates, 2 changelog entries and 1 news mention.
From picking favorites to designing experiments: how ML rethinks variant selection
Discusses how ML transforms variant selection in protein engineering campaigns from heuristic to experimental design.
How does AI change the first round of antibody optimization?
Explores AI impact on initial antibody optimization rounds, shifting from brute force to guided approaches.
Introducing Guided Rounds
New structured workflow for ML-guided protein engineering campaigns, embedding expertise into each step.
Zero-shot antibody diversification with Cradle
Enables antibody diversification without training data using zero-shot ML predictions.
Drug discovery leader Marcus Schindler joins Cradle's Advisory Board
Former Novo Nordisk CSO Marcus Schindler appointed to advisory board for biologics strategy.
Viability Score
How well maintained and how widely used is Cradle Bio? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: July 2026
How we score →Key Features
- Generative AI protein candidate generation
- Multi-property co-optimization (affinity, stability, expression, activity, specificity)
- Guided Rounds for structured ML-driven campaigns
- Zero-shot antibody diversification
- Multi-property trade-off visualization tools
- Custom predictors (beta) for internal models
- Compounding model learning from each wet lab round
- Round tracking from generation to experimental results
- Support for antibodies, enzymes, vaccines, peptides
- Privacy-first AI: proprietary data never trains public models
- SOC 2 compliant security
- Single Sign-On (SSO) for Google and Microsoft
- In-house wet lab for model validation
- Dedicated support from scientists and ML experts
About Cradle Bio
Cradle is an AI-driven protein engineering platform that helps biopharma and industrial biotech teams design, optimize, and develop proteins faster. By combining generative AI with proprietary experimental data, it enables scientists to improve properties like binding affinity, stability, expression, activity, and specificity across antibodies, enzymes, vaccines, and peptides. Features include Guided Rounds for structured ML campaigns, zero-shot antibody diversification, multi-property trade-off visualization, and custom predictors (beta). The platform compounds learning from each wet-lab round, reportedly accelerating timelines by 2–12x. Cradle prioritizes data privacy: your sequences and data remain secure, never used to train public models, and the platform is SOC 2 compliant with SSO support. Unlike generic AI tools, Cradle focuses on multi-property co-optimization and enterprise-grade security, making it ideal for R&D teams needing scalable, private protein engineering.
Behind the Verdict
Cradle stands out for combining generative AI with proprietary experimental data in a private, secure environment. Its Guided Rounds and zero-shot antibody diversification are notably innovative. The platform's ability to co-optimize multiple properties and compound learning from each round can drastically reduce development time. The recent addition of trade-off visualization tools and the appointment of drug discovery leader Marcus Schindler to the advisory board signal a strong commitment to expanding capabilities. However, the lack of transparent pricing and the need for your own wet-lab data to benefit from compounding learning may deter smaller or early-stage teams. Cradle is best suited for established biopharma and industrial bio organizations that can invest in a full-scale AI partnership.
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Real-world workflow fit
Concrete scenarios for the personas Cradle Bio actually fits — and what changes day-one when you adopt it.
You have a lead antibody with suboptimal binding affinity and developability. Using Cradle's Guided Rounds, you generate 100 variants, test them in the wet lab, upload results, and let the model compound learning for the next round. After 3 rounds, you identify a candidate with 10x improved affinity and maintained stability.
Outcome: Improved antibody candidate with multi-property optimization, achieved in weeks rather than months.
You need an enzyme with higher thermostability and activity under industrial conditions. Cradle's multi-property trade-off visualization helps you balance stability and activity. You run 2 rounds of generation and testing, resulting in an enzyme that performs at 60°C with 50% higher yield.
Outcome: Industrial-ready enzyme variant with accelerated development timeline.
Your vaccine antigen is thermally unstable, limiting shelf life. Using Cradle's zero-shot diversification, you generate variants predicted to be more stable without initial data. After one round of validation, you obtain a variant with a 2.5°C increase in melting temperature.
Outcome: Stabilized antigen with improved thermostability in a single round.
Use Cases
- Generate antibody candidates with improved binding affinity and developability
- Optimize enzyme stability and activity for industrial biocatalysis
- Design vaccine antigens with enhanced thermostability
- Engineer therapeutic peptides meeting multiple property constraints
- Rescue stalled protein engineering campaigns by exploring diverse strategies
Models Under the Hood
as of 2026-07-31
Limitations
- No public pricing or API details are available.
- The platform is web-only and likely requires a sales conversation for access.
- You need your own experimental data to benefit from compounding learning—if you have no wet-lab results, Cradle's value drops significantly.
- Model capabilities and limits are not disclosed beyond general claims.
as of 2026-07-30
Verification history
We have re-verified Cradle Bio 14 times since . Each pass re-reads the vendor's own pages and updates only what actually changed.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 14 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where Cradle Bio's pricing actually pencils out — and where peers do it cheaper.
Cradle is enterprise-priced and suited for large biopharma and industrial bio teams with dedicated budgets. It is more expensive than open-source or academic tools but offers secure, private, multi-property optimization that cheaper alternatives may lack.
Setup time & first value
How long it actually takes to get something useful out of Cradle Bio — broken out by persona, not the marketing-page minute.
Biopharma teams with existing experimental data can set up Cradle in under a day by uploading sequences and historical results. Initial candidate generation starts immediately, with full pipeline integration taking 1-2 weeks for team onboarding.
Switching to or from Cradle Bio
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From manual protein engineering: Cradle provides templates to import your sequence and property data, replacing spreadsheets with a structured ML campaign.
- ↗To open-source models: Export your final sequences and property data from Cradle; the platform does not lock you in, but the proprietary ML models are not portable.
Resources & Guides
Tutorials & Learning
Official links
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Common stack mates teams adopt alongside Cradle Bio, with the specific reason each pairing earns its keep.
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