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AI-Guided Crispr engineering

Higher on-target activity. Lower off-target. In fewer rounds.

Optimize Cas proteins, base editors, and other CRISPR systems for activity, specificity, expression, and thermostability — in parallel. From <25% to 68% on-target editing in three rounds. From 100:1 to 750:1 specificity ratio in two.

Read CRISPR case studies

Explore platform

CRISPR engineering means optimizing for safety and efficacy at the same time

Mutations that boost on-target activity often increase off-target editing too. Stabilize a Cas variant for delivery, you risk losing catalytic activity. Improve expression, the specificity profile shifts. And large screening campaigns — even ones testing thousands of variants — frequently top out below the threshold needed for therapeutic development.

Enzyme discovery before

Project design

Target ID

Variant generation

Optimization

Application testing

Lead Op

Scale up

Enzyme discovery with Cradle

Project design

Target ID

AI protein engineering

AI Protein Engineering

Scale up

Preclinical

From marginal editing to therapeutic-grade candidate

Fewer rounds

Extract signal from your existing screening data

Cradle ingests your prior screening and rational design data — including campaigns that didn't yield a clinically viable candidate — and learns the sequence-function relationships your team has already paid to generate. On one CRISPR system, 288 candidates across three Cradle rounds outperformed a 3,000+ variant screening campaign, taking on-target activity from <25% to 68%.

Better CAS variants

Improve activity and specificity simultaneously

Cradle treats off-target editing at multiple genomic sites as constraints to minimize, alongside on-target activity as the primary objective. Your team finds the rare mutational combinations that selectively enhance target discrimination — outcomes structural design and exhaustive mutagenesis often miss. On a six-property optimization (one on-target, five off-target sites), Cradle delivered 75% on-target with 0.1% worst-site off-target — a 7.5× improvement in specificity ratio.

Built for biologists

An intuitive workbench for any enzyme class

Your scientists run campaigns directly through the UI. Your comp bio team extends the platform via API with their own predictors and scoring. Your sequences and model weights stay yours.

Fewer rounds

Extract signal from your existing screening data

Better CAS variants

Improve activity and specificity simultaneously

Built for biologists

An intuitive workbench for any enzyme class

Your scientists run campaigns directly through the UI. Your comp bio team extends the platform via API with their own predictors and scoring. Your sequences and model weights stay yours.

Selected properties

If you can assay it, you can optimize it with Cradle.

Set multiple objectives and let Cradle find variants that balance them - starting from as few as 96 variants per round.

Editing performance

On-target editing activity, off-target editing across multiple sites, specificity ratio, PAM compatibility

Expression & stability

Expression yield in production hosts, thermostability (Tm), solvent and buffer tolerance

Delivery & format

Protein size, AAV-compatibility, RNP stability

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CASE STUDIES

Wet lab validated.
Trusted in 50+ active programs.

Enzyme case studies

Using AI to produce vaccine adjuvants without cutting down rainforest

Enzyme case studies

Improving haloalkane dehalogenase thermostability by +20 °C while enhancing activity and expression

Enzyme case studies

'Align to Innovate' benchmark: state-of-the-art enzyme engineering with fully-automated GenAI

Enzyme case studies

Case study: design better P450s 4X faster by combining AI-generated mutations with human expertise

Enzyme case studies

Using AI to produce vaccine adjuvants without cutting down rainforest

Enzyme case studies

Improving haloalkane dehalogenase thermostability by +20 °C while enhancing activity and expression

Enzyme case studies

'Align to Innovate' benchmark: state-of-the-art enzyme engineering with fully-automated GenAI

"Through our partnership with Cradle, we are embedding advanced Al directly into how we innovate, enabling our teams to shorten development time and bring real-world biosolutions faster to market."

Claus Fuglsang Crone

Chief Scientific Officer, Novonesis

Case studies

Using AI to produce vaccine adjuvants without cutting down rainforest

Case studies

Improving haloalkane dehalogenase thermostability by +20 °C while enhancing activity and expression

Case studies

'Align to Innovate' benchmark: state-of-the-art enzyme engineering with fully-automated GenAI

Case studies

Using AI to produce vaccine adjuvants without cutting down rainforest

News

Drug discovery leader Marcus Schindler joins Cradle’s Advisory Board

Guides

Product

Visualizing trade-offs in multi-property protein optimization

Same experimental workflow.
Better results.

With everyone in the same workspace, results compound across your organization. Same data. Same models. Same learning loop. New results.

API and Web Interface

Granular access controls

Unlimited seats

Web Interface

For wet lab scientists

Add your domain expertise and AI generate candidates for lab testing in just a few clicks. Upload experimental results to improve your project-specific AI automatically.

Learn more about the Cradle platform

API Access

For computational teams

Run Cradle with an API and scale your expertise without the DevOps overhead. Focus on novel design strategies, not routine requests and endless configuration.

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