Collection
A living shortlist of newer AI-native biology companies worth following across protein design, drug discovery, pathology, and scientific research tooling.
causaly.com
A life science AI platform combining biomedical knowledge graphs, scientific search, and research copilots for R&D teams.
owkin.com
An AI-biotech company combining patient data, biological reasoning models, and agentic systems for discovery and clinical programs.
aqemia.com
A pharmatech company combining deep physics and AI to accelerate small-molecule discovery.
bioptimus.com
A company building biology foundation models, including widely discussed models for pathology and multimodal biology.
xaira.com
An AI drug-discovery company building predictive and agentic models across the full discovery and development stack.
latentlabs.com
A frontier AI lab building generative models for proteins, antibodies, and broader molecular biology design tasks.
profluent.bio
An AI-first protein design company using generative models for novel proteins and gene-editing systems.
cradle.bio
An AI protein-engineering platform used by biopharma and industrial bio teams to design and optimize protein candidates faster.
chaidiscovery.com
An AI drug-discovery company focused on molecule and antibody design with structure-aware models.
evolutionaryscale.ai
A frontier AI company building large protein models and generative systems for understanding and designing biology.
This collection currently includes 10 indexable resources, making it useful when you want a practical set of related options around one workflow or theme.
A living shortlist of newer AI-native biology companies worth following across protein design, drug discovery, pathology, and scientific research tooling. The collection emphasizes how those resources fit together, not just how they exist as isolated entries.
The AI-biology market moves too fast for static vendor pages. This collection is for readers who want a clean way to track the newer companies shaping the conversation right now.
Use it when you need a tighter watchlist of model-first biotech companies, biology foundation-model teams, and AI-heavy research platforms.