- Accessible protein design for wet labs
- Concentrates on drug discovery depth over broad coverage
- Scales to organization-wide healthcare rollouts
Cradle
AI protein design for wet labs
SF7.5
SF Score editorial score across features, ease, and value, based on public reviews and product research. Learn more →
Support protein engineering programsProtein engineering and biotech teams
Support protein engineering programsProtein engineering and biotech teams
Best for
Protein engineering and biotech teams
Pricing
Custom
SoftFinders Score
7.5 / 10
Overview
What is Cradle?
Cradle is an AI protein engineering platform for protein engineering and biotech teams, supporting the design and optimization of proteins for research programs.
- Research focus: It supports R&D acceleration and computational biology rather than guaranteed clinical outcomes, with candidates still requiring downstream validation and trials.
- Best-fit environment: Protein engineering and biotech teams may benefit most when accessible protein design fits established wet-lab workflows and in-house research programs.
- Engagement model: Access typically runs through pharma partnerships rather than self-service subscriptions, making collaboration structure, data requirements, and expected timelines to validated leads important buying considerations.
- Commercial model: Pricing is sales-led and scoped per buyer rather than publicly posted, with value shaped by the depth of internal protein programs.
Cradle is best assessed as an accessible protein design layer whose fit depends on wet-lab integration, in-house expertise, and research objectives.
KEY FEATURES
What you get out of the box
Target Discovery
Identifies potential drug targets from biological data
Molecule Design
Generates and ranks small molecule candidates
Protein Modeling
Predicts and designs protein structures
Knowledge Graph
Connects biological and chemical knowledge sources
Virtual Screening
Screens compound libraries against targets
Literature Intelligence
Mines biomedical literature for relevant evidence
USE CASES
Where teams put it to work
Support protein engineering programs
Mine literature for research signals
Run virtual screens against targets
Collaborate with pharma partners
Bridge AI design and wet lab cycles
Identify drug targets from biology data
Editorial Take
What we like, and what to verify
- Best value needs in-house protein programs
- Drug success still depends on downstream trials
- Pricing is sales-led and needs scoping upfront
Screenshots
A look inside
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FAQ