Cradle

The generative model is the product and the delivery mechanism is software rather than a service wrapper. The platform inverts conventional protein engineering by taking a desired property and producing candidate sequences, rather than iterating experimentally from a natural starting point, and the company's own framing of protein design as a digital service is accurate to what is sold. The wet lab exists to expand the foundational models across additional modalities and properties, which is the correct direction of dependency for an A grade: the lab serves the model, not the reverse.

The platform proposes and the customer's scientists dispose, with the stated value being fewer experimental rounds rather than no experimental rounds, so wet lab confirmation remains the structural check. One disclosed data point cuts the other way and is worth knowing: in the Align to Innovate competition the company's enzyme models were generated in an automated fashion without expert intervention, which indicates the system can operate with minimal human steering when the problem is well posed. Held at B because no confidence thresholds, failure rates or documented guidance on when a design should not be trusted were located.

The approach is described concretely, covering generative design from specified properties, 3D structure prediction, thermostability and codon expression optimization, and models trained on each customer's own data rather than a single shared model. Held at B because no peer reviewed methods paper establishing core platform performance was located in this review and no model cards or published benchmarks were found. The partial offset is that the company entered a third party competition where its output could be measured against others, which is a form of external exposure most peers avoid, though the result is company reported rather than independently published here.

Operational evidence is strong and unusually well specified. As of the December 2025 update the platform served six of the top 25 global pharmaceutical companies across more than 50 R&D programmes, with customers named rather than anonymized, including Johnson & Johnson, AbbVie, Novo Nordisk, Novonesis, Grifols and Lundbeck, and the earlier Series B disclosure of 21 customers and 31 molecules in development gives a growth trajectory that can be checked against later statements. More notable for this index, the company submitted to third party comparison: in the Align to Innovate competition its enzyme models outperformed or ranked in the top two among roughly 30 teams drawn from industry and academia. Entering an open benchmark where you can lose is rare in this category and the index treats it as a positive evidence signal. Held at B rather than A because the competition result is company reported, no peer reviewed outcome study was located, the stated R&D speedups of 1.2 to 12 times are vendor generated, and no therapeutic designed on the platform with human data was identified.

Not applicable in the provider sense and rated accordingly rather than penalized. The platform operates on protein sequences, structures and customer assay data with no patient records in the workflow. The stewardship question that matters here is customer intellectual property rather than PHI, and it is addressed unusually directly on the commercial and governance axes.

Not applicable. Customers are pharmaceutical, biotechnology, agricultural, food and chemical R&D organizations licensing design software, not covered entities transferring protected health information.

No SOC 2, ISO 27001 or equivalent attestation was located and no trust center was found. A distinction worth holding during diligence: the company publicly emphasizes data security and intellectual property protection and commits that customers retain full ownership of proteins engineered on the platform, but an IP ownership commitment is a contractual term, not a security attestation, and the two answer different questions. Given that customers upload proprietary sequence and assay data into a multi tenant software product rather than into a bilateral collaboration, an attestation would carry more weight here than for the partnership only platforms in this category.

Nothing to assess rather than something assessed poorly. The platform is design software, is not a regulated medical device, and the company maintains no disclosed proprietary clinical pipeline. Regulatory standing for any protein designed on the platform sits with the customer that owns it, which is the direct consequence of the IP ownership term, and customer assets are not publicly attributed to the platform.

No formal AI governance framework or bias disclosure was located, but the company's disclosed architecture answers the sharpest governance question in this category better than most. Where a shared model improving on every customer's data creates an obvious conflict, Cradle states that models are trained on each customer's own data and tailored to their specific needs, and that customers retain full ownership of proteins engineered on the platform. Buyers should still confirm in contract whether any learning generalizes across tenants and what happens to trained artifacts at termination, since the public statements describe intent rather than architecture. The domain relevant bias question is that a model trained largely on characterized proteins will perform unevenly on sequence space with little experimental coverage, and no performance breakdown by protein family or data density was located.

Not applicable in the provider sense, with no EHR touchpoint or clinical workflow surface. The research equivalent is the platform's own interface, which is designed for customer scientist teams to operate directly rather than requiring a computational biology intermediary, and that accessibility is the company's stated reason for calling itself enterprise software rather than a service.

Genuinely a deployed software product rather than a partnership, which is rare in this category: customer scientist teams use the platform directly across more than 50 concurrent R&D programmes, and the company has built out dedicated teams in the United States to support deployment alongside its European base. Held at B because no on premise or private cloud option was located and no regional data residency terms were published, so proprietary sequence and assay data does move into the vendor environment. Compare Iktos, which offers on premise and virtual private cloud implementations and therefore scores higher on the same question.

No pricing is published, which is the ceiling on this grade, and unlike the partnership only platforms in this category a rate card here would be both possible and meaningful since the product is licensed software. What is published is better than most: a specific and checkable customer footprint (six of the top 25 pharmaceutical companies, more than 50 R&D programmes, with major customers named), a full funding history (24 million dollar Series A, 73 million dollar Series B led by IVP with Index Ventures and Kindred Capital, over 100 million dollars total), and one genuinely important commercial term stated openly rather than buried in negotiation, that customers retain full ownership of any proteins engineered on the platform. Publishing the IP position is the disclosure that most affects a buyer's decision here.

The widest applied coverage in this category after Schrodinger, and unlike most peers the breadth is across industries rather than only therapeutic areas. Disclosed use spans therapeutics, diagnostics, agriculture, food production and chemical manufacturing, with customers reflecting that range: Johnson & Johnson, AbbVie, Novo Nordisk and Lundbeck on the therapeutic side, Novonesis in industrial enzymes and Grifols in plasma derived medicines. Modality is proteins and biologics rather than small molecules, which is the real boundary, and the company is expanding its wet lab specifically to extend the models into additional protein modalities.