Build a closed discovery loop of AI-to-biology
We’ve built the experimental reasoning language AI needs to understand biology. Pathways seen in action, in space and time, made computable for AI.
The Biology GPU
The BioGPU’s Visual Biology Agent transforms AI models into experimental self-driving discovery engines, creating an explainable reasoning loop grounded in real biology that discovers causal targets and better drugs.
Visualization layer: Proprietary visualisation modality that directly images biological pathways and mechanisms in action inside cells at AI scale.
Biology layer: Large-scale experimental infrastructure that enables AI models to visually compute inside cells and reason experimentally about disease mechanisms.
Compute layer: A Visual Biology Model trained on more than 2 billion proprietary pathway images, designed to recognize active biological pathways in healthy and diseased cells. Its runtime can be deployed in a customer’s private cloud.
Access layer: The BioGPU Agent connects AI models (LLMs) to the BioGPU infrastructure.
Visual Biology Model
Trained on 2B+ process visualizations, it recognizes active pathways in cells.
Enabling experimental reasoning in real biological pathways.
Visual mRNA Biology Model
Trained on mRNA biology regulatory visualizations mechanisms.
Enabling the discovery of target modulators through mRNA biology.
Visual Biology GPU Agent
LLM’s research partner for experimental reasoning inside cells
The functional biology modality AI needs, at the scale it thinks
A unified experimental imaging modality that makes functional biology at scale ready for AI.
Giving models explainable insights to experimentally reason on disease-driving mechanisms.
inside cells
What AI can do with the Biology GPU
+ Additional use cases in mRNA biology with a specialized mRNA neural network
Partner with Anima to Build an
End-to-End AI-to-cell Stack
See and compute on pathways inside real biology.
Identify disease driving pathways, novel targets and drugs that modulate the phenotype.