How do their growth rates compare?

Cradle has a month-over-month growth rate of -22.3%; Whimsical has -18.7%.

How does pricing compare?

Cradle: Contact for Pricing. Pricing is not publicly listed. Cradle uses a contact-for-pricing model where teams discuss their project and program scope directly with the company; a licensing track and API access are offered alongside the core platform. Whimsical: Freemium. Freemium. The Free plan costs $0 and includes unlimited boards and members but limits output to 50 board objects and 50 doc blocks per month with export watermarks and 7-day history. Pro is $10 per editor/month billed annually ($12 monthly) with unlimited objects, no watermarks and 90-day history. Business is $20 per editor/month annually ($24 monthly) and adds private teams, SAML SSO, SCIM, security controls and unlimited version history. Viewers and guests are always free; students, teachers and non-profits get special pricing.

What are alternatives to Cradle and Whimsical?

Other tools in related categories include Miro, Dr.Oracle, Taskade, Boardmix, Uizard.

Cradle vs Whimsical — Traffic (16.99K vs 966.9K), Pricing & Verdict

Open AI Tools

Cradle vs Whimsical — Traffic (16.99K vs 966.9K), Pricing & Verdict | Open AI Tools

Side-by-Side Traffic & Specification Matrix

Dimension / Metric	Cradle	Whimsical
Official Domain	cradle.bio	whimsical.com
Pricing Model	Contact for Pricing	Freemium
Monthly Visits	16.99K (16,993)	966.9K (966,895)
MoM Traffic Delta	-4.88K (-22.3%)	-222.85K (-18.7%)
Primary Market & Share	🇳🇱 Netherlands (47.6%)	🇮🇳 India (19%)
Direct Visits / mo	6.21K	602.36K
User Rating	4.5	4.7
Supported Platforms	Website	Website

Cradle

Engineer better proteins, faster, with AI

De novo protein design

Start from a target or your own sequence and have Cradle design an optimized plate of candidates informed by your data and domain knowledge.

Parallel multi-property optimization

Improve efficacy, developability, and manufacturability in parallel rather than one property at a time, compressing time to a target profile.

Closed-loop learning from experimental data

Every round incorporates results from the previous one, so experimental data compounds across campaigns and prior failed programs stay useful.

Full API access

Everything in the web application is exposed through the API, so computational teams can script campaigns and wire Cradle into existing pipelines.

Strengths & Pros

+Optimizes multiple protein properties in parallel rather than sequentially, which can cut the number of experimental rounds
+Learns from a customer's own experimental data, including negative and failed results
+Covers antibodies, enzymes, vaccines, and peptides in one platform
+Full API parity with the web app supports computational and automated workflows