Life Sciences AISeedWorkflow signalℹ29Output Biosciences
Output Biosciences is building Large Biological Models, generative AI architectures designed to handle the long, nonlinear, fragmented data of biological systems across molecules, cells, and organisms.
Why people are saving it
Relevant for biotech researchers and drug discovery teams tracking generative AI built specifically for biological data structures.
What they're building
Output Biosciences is developing Large Biological Models—generative AI architectures designed to process the long, nonlinear, and fragmented data that spans molecules, cells, and organisms.
Founders
Adi Mashiach, MD
Co-founder
Mirella Mashiach
Co-founder
Foundation model usage
Output Biosciences applies models to biological data where retrieval, structure, and multimodal reasoning matter.
NYC footprint
Output Biosciences is part of the New York City AI startup scene, with a profile focused on its market category, stage, and product signal.
Funding
Latest funding: Seed (YC S21). Lead investor: Y Combinator.
Platform / OpenAI fit
Strong fit for multimodal reasoning, biological data retrieval, molecule and protein analysis, structured extraction, and research copilots.
Notes
Output Biosciences is tagged workflow signal based on buyer clarity, repeat workflow signal, public activity, and fit with the AI Atlas map.
Related NYC startups
Protein interaction maps for drug discovery
Proxima Bio, formerly VantAI, is an AI-native platform for proximity-based drug discovery, mapping protein-protein interactions to design medicines that reshape protein networks rather than inhibit single targets.
Life Sciences AIWorkflow signalℹ83viewsRecent Activity
Protein interaction maps for drug discovery
Serinus Biosciences uses a knowledge-primed AI engine to design cancer combination therapies by mapping how tumor cells evolve treatment resistance and identifying molecules that override resistance escape routes.
Life Sciences AIWorkflow signalℹ124viewsRecent Activity