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Strand AI

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Multimodal foundation models to predict uncollected patient biology

Winter 2026Founded 20252 peopleSan Francisco, CA, USA
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Biodata Foundation Models for Clinical TrialsSaaSPharmaceutical companies and clinical research organizationsLow competition
Moat
Proprietary foundation model trained on spatial biology data; rare multimodal biodata training approach.
Key risk
Unproven efficacy; regulatory approval for clinical use; limited customer base (pharma only).
Why now
Pharma under pressure to accelerate drug launches; multimodal foundation models now viable.
Competitors
Emerging space, some biodata AI startups

About

Strand AI develops foundation models to generate missing bio-data about patients. With this imputed data, pharmaceutical companies can select better patients for their drug trials and shave months from their drug launch timelines. Weโ€™ve already trained a multimodal foundation model that integrates spatial biology modalities, beating SOTA at a fraction of the cost.

Founders ยท 2

Yue Dai
Yue DaiFounder
Microsoft

Cofounder & CEO at Strand AI ex-Pathos AI, Enable Medicine, Microsoft Research, Element AI. Trained foundation models for biology on the largest patient dataset in existence.

Oded Falik
Oded FalikFounder

Cofounder & CTO at Strand AI Ex-Enable Medicine Building foundation models to enrich biology data and improve patient outcomes. Oded Falik, CTO, was the Tech Lead for Enable Medicine's spatial biology platform, scaling to 12B+ single-cell annotations and petabyte-scale pipelines. Programming since 8 years old, published first app on iOS app store at 11 years old.

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