From Foundation Model to Biological Product
How we’re building products on top of genomic foundation models, using distribution to discover the workflows community will rely on.
Read →Genome-scale AI for biology
Programming biology with genomic intelligence.
We build ultra-long-context genomic foundation models to predict disease risk, explain heritability, and design actionable edits from whole-genome and multi-omics data.
- A · adenine
- T · thymine
- C · cytosine
- G · guanine
Mission
Explain the genome. Predict disease. Design the next intervention.
Models
Foundation models
Ultra-long context architectures pretrained on whole genomes to capture regulatory logic across megabases.
Prediction
Predictive health
Variant effect, expression, and disease-risk prediction grounded in multi-omics, calibrated to clinical use.
Design
Actionable design
From hypothesis to edit — close the loop between in-silico prediction and wet-lab validation faster.
Blog
From the blog
Designing the Control Layer of Gene Therapy: Introducing Promoter Atlas
From a biological specification to ready-to-test promoter sequences using computation for the broad search and experiments for focused validation.
Read →The Next AlphaFold Won’t Design Drugs. It Will Find Targets
Evolution has already generated the data. The next challenge is learning what it means.
Read → Team
An interdisciplinary team spanning AI, biology, and software infrastructure.
Julia Kiseleva, PhD
Product vision and incremental experimentation.
Benjamin Fishman, PhD
Wet-lab validation and genomic model science.
Mikhail Burtsev, PhD
Ultra-long context models and memory architectures.
Alex Boldakov
Data platforms, infrastructure, and scale.
Advisory
Guidance from leaders in AI and health.
Eric Horvitz, MD, PhD
AI-for-health strategy and ecosystem leadership (Microsoft CSO; founder of Stanford AI100; former AAAI President).
Natalia Vassilieva, PhD
AI infrastructure and large-scale ML leadership across scientific and health applications (VP & Field CTO, ML at Cerebras Systems; former Software and AI research leader at Hewlett Packard Labs).
Partners
Building with partners across cloud, data, and biology.
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Member of AWS Frontier AI
Cloud infrastructure and enterprise go-to-market.
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Healthcare technology collaboration
Clinical data infrastructure and hospital distribution.
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Biological design collaboration
Model-driven discovery and experimental validation.
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Scientific-agent integration
Genomic models embedded into AI-powered research workflows.
Integrations
Where you can use us.
Our models already answer from inside these tools. Pick the one you work in.
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ChatGPT
Add the Genomic Intelligence app and run the tasks in a conversation.
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Proto
Sequence scoring in proto-tools, the tool catalogue behind Proto.
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Databricks
Our MCP server, a free listing on Databricks Marketplace.
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Phylo
Enable our models as an external integration in Biomni Lab.
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ClawBio
Our prediction skills ship with the open-source bioinformatics agent.
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K-Dense
A genomic-intelligence skill in the scientific agent skill library.
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ToolUniverse
Opt-in tools your AI scientist can load from the tool library.
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BioClaw
A query-genomic-intelligence skill in the bioinformatics assistant.
The server is listed in the MCP Registry, so the same models answer from any MCP client, and directly over the REST API.
Interested in Genomic Intelligence?
Investors, partners, and researchers — let's talk about programming biology together.