Design better proteins

Cradle helps biologists design improved proteins in record time using powerful prediction algorithms and AI design suggestions.

Protein structure illustrationProject lead
Protein engineer

Ribonuclease inhibitor

RNase inhibitor

Bioinformatician

Details

  1. Save days of work.

    Visualize, analyze, and predict candidates’ potential all in one place. In other words, know what works out in the real world – faster.

  2. Improve with every round.

    Train the Cradle AI with results from your wet lab to build a tailored model that improves candidates with each round of testing.

  3. Low throughput, big results

    Use Cradle for any project. No high throughput assay? No problem. Get impressive results between rounds with just a 96 well plate.

  4. Unlimited candidates   

    Choose what to improve, then generate quality candidates in just one click. Not feeling the results? Click again.

Thermostability icon
Structure prediction icon
Codon optimization icon

AI-assisted design tools

Predict a protein's 3D structure, generate new sequences with improved thermostability, optimize codons and much more soon...

  • Protein structure illustration
    Name: Beta-amylase
    Variant: mutant1

    3D structure prediction

    Predict the structure of an individual sequence or multimer with AlphaFold 2. Optimized for speed without compromising on accuracy.

  • Melting point
    16%

    Thermostability

    Optimize the thermostability of your proteins with models trained on large datasets. Get even better suggestions after a round of experiments in the lab.

  • Codon graph

    Codon optimization

    Optimize your protein’s codons for better expression. Go beyond codon usage tables and leverage machine learning models that have seen DNA-Protein-sequence-pairs from your host.

    • Stability

      Future

      Design proteins that do better in harsher environments by improving their stability in solvents.

    • Activity

      Future

      Want your enzyme to go faster? Improve the rate by which your enzyme performs its reactions.

    • Specificity

      Future

      Design proteins that fit like a glove by optimizing their specificity.

    • Affinity

      Future

      Improve your protein’s affinity to increase protein-protein interactions.

    • Multiobjective

      Future

      Optimize all of the above by setting targets for multiple phenotypes simultaneously and let the models find an optimum.

Private.
Secure.
Yours.

Cradle keeps your sequences and data private and secure while giving you full ownership of all intellectual property.

  • Private by design

    We think your sequences are incredibly valuable, but we’ll never know. Why? Only you and people you invite from your organization can access sequence data.

  • Safe & secure

    As industry veterans, we know it all comes down to security. Cradle uses bank-grade level of security to keep your data safe.

  • Own your IP

    We keep IP a lot simpler than we do security. How simple? It’s yours, you own the IP. How about royalties? Nope. You only pay for users and usage of our tools.

The team

Cells – the factories of the future.

We believe cells can theoretically produce almost anything, from fabrics to food, fuel and medicines. Designing cell-factories is hard, but our tools and machine learning models can make it easier. Our mission is to ultimately help replace traditional farms and factories for a more sustainable world.

  • Jelle makes sure that Cradle's products are easy to use.

    He previously designed the first apps for Uber, Booking.com and CataWiki.

  • Elise de Reus

    Elise de Reus

    bioengineering

    Elise turns machine learning-generated sequences into physical proteins and tests how they behave.

    She previously engineered microbes in high throughput at Zymergen and Perfect Day. She holds a PhD in fungal synthetic biology.

  • Cradle team hike in the Swiss alps

    Code. Hike. Sleep. Repeat

    Winter 2021 offsite
  • Sytske finds out what our users need and learns from their feedback on our tools.

    She was previously researching people at Uber and Facebook/Meta and teaching statistics in San Quentin Prison. She holds a PhD from the University of Cambridge.

  • Tomasz makes the machine learning workflows available to the end users through the Web-app and APIs.

    He was previously front-end lead at Brainly and software engineer at Google and Base CRM.

  • Cradle offsite in Friesland

    Boatin’ to offsite dinner

    Fall 2022 offsite
  • Martin Tschechne

    Martin Tschechne

    machine learning

    Martin teaches Cradle’s algorithms how to design even fancier proteins.

    Before joining Cradle he worked at Disney and JP Morgan. He holds a Masters degree in Computational Science and Engineering from ETH Zurich.

  • Daan van der Vorm

    Daan van der Vorm

    bioengineering

    Daan tests if our AI generated proteins actually do what they are supposed to.

    Previously positioned at Nostics, he utilized lasers and nanotech to nurture an assay based on surface enhanced Raman scattering for the detection of COVID and bacteria.

  • Harmen van Rossum

    Harmen van Rossum

    bioengineering

    Harmen automates the lab.

    He previously engineered microbes at DSM and Zymergen. He has a PhD in metabolic engineering from Delft University of Technology.

  • Luba pairs up with Stef on doing everything else that needs to be done (and some more).

    Before joining Cradle, she built teams at RepRisk (ESG data), ran projects at WWF, and consulted for BCG. She holds a law degree from McGill and an MBA from Queen's (Canada).

  • Franzi Geiger

    Franzi Geiger

    machine learning

    Franzi teaches large language models to understand proteins.

    She was previously a machine learning engineer at Google, IBM and Oracle and did computational biology research at MIT.

  • Cradle offsite in Friesland

    Boatin’ to offsite dinner

    Fall 2022 offsite
  • Ena Škopelja

    Ena Škopelja

    machine learning

    Ena is a machine learning engineer dabbling in some fullstack development as well.

    She studied molecular biology and has a Masters degree in mathematics and computer science.

  • Adam Weber

    Adam Weber

    engineering

    Adam builds easy to use and responsive interfaces for people who want to use our tools from a browser.

    He was previously a frontend engineer at Hiya, IBM Video Streaming and Wunderman Thompson Budapest.

  • Arthur Lindoulsi

    Arthur Lindoulsi

    machine learning

    Arthur loves solving puzzles, and considers protein design to be the most worthy puzzle of all!

    He was previously in Novartis where he worked on diverse life science projects using machine learning and holds a masters degree from Ecole Centrale Paris.

  • Eli Bixby

    Eli Bixby

    machine learning

    Eli makes sure our models and algorithms are doing what we think they are doing, and he keeps an eye out for the latest and greatest techniques in the literature.

    He was previously at Google (Brain, Accelerated Science, Cloud) working on biological sequence design, AutoML, and natural language understanding. He studied mathematics, computer science, and biochemistry.

  • Daniel is the adult supervision. When the kids are good, he squeezes in as much coding as possible.

    He previously worked at the Medical Bioinformatics Lab at ETH, he was CTO at Daedalean AI and Senior Staff Eng at Google. He holds a PhD in applied mathematics (genetic algorithms).

  • Max decides where buttons go, what they do, and how they look.

    He previously helped design user interfaces at Klarna, Citrix and Leo Pharma.

  • Cradle offsite house in the alps

    Swiss offsite perks: views

    Winter 2021 offsite
  • Emily Soley

    Emily Soley

    bioengineering

    Emily builds DNA, uses microbes for protein expression, and tests protein behavior.

    She previously worked on protein expression, purification and refolding at Zymergen, as well as NGS target enrichment at Twist.

  • Stef does everything else that needs to be done.

    He was previously part of product leadership at Google Research & Machine Intelligence. At Google X his focus was on AI infrastructure and developer tooling applied research.

Backed by the best

We are funded by leading investors Index Ventures and Kindred Capital, as well as long list of world-class advisors and angel investors.

Read funding announcement
Index ventures logo

Index Ventures

Index helps entrepreneurs turn bold ideas into businesses that have a long-lasting positive impact on the world.

"We love Cradle because it is enabling a new wave of progress that aims to improve the health of both humanity and the planet."
Kindred logo

Kindred Capital

Kindred is an early investor in LabGenius, Ori, Eleven Tx, and others.

"We believe the next $100Bn opportunity will be built at the intersection of biology and computation, and that Europe can play a leading role on the global stage."

Angel investors

  • Emily Leproust

    CEO of Twist Biosciences

  • Steve Crossan

    SVP AI at GSK, former Head of Product at Deepmind and co-founder of Alphafold project

  • Adriaan Mol

    Founder at Mollie & Messagebird

  • John Zimmer

    CEO & Founder at Lyft

  • Tim Geistlinger

    Chief Scientific Officer, Perfect Day

  • Mehdi Ghissassi

    Director of Product at Deepmind

  • Patrick Hsu

    Professor at Berkeley & Founder of Arc Institute

  • Feike Sijbesma

    Honorary Chairman and former CEO at Royal DSM

  • Sylvain Gariel

    Founder & CEO at DNA Script