Develop groundbreaking models that unlock insights from vast multimodal data sets.
Improve understanding of disease biology and accelerate timelines for drug discovery.
Design novel mutations, model complex effects, and speed your therapeutics pipeline.
Train your own AI model on proprietary data from clinical trials, scientific literature, and molecular databases.
Prompt your model to discover patterns and relationships between data like protein sequences, biological systems, and disease states.
Ensure privacy and regulatory compliance by keeping your workflow in-house. Maintain full control of your data and total ownership of your AI model.
Transform the design, optimization, and synthesis of molecules and power virtual creation of new and lead candidates
Predict drug protein interactions and determine drug effectiveness once a potential new drug has been identified
Use chatbots for participant pre-screening; identify latent trends through automated document analysis; generate synthetic datasets that preserve patient privacy
Enable comprehensive genome sequencing and molecular biomarker analysis; power high-throughput imaging and diagnostics
Our system optimizations drastically reduce the amount of compute needed to generate high-quality models.
Our flexible platform makes state-of-the-art deep learning infrastructure available to anyone with a few command lines.
Train advanced AI models in any cloud environment with complete data privacy and full model ownership.
One-click training and one-click inference reduce the time needed to develop complex AI models by orders of magnitude.
"Generative AI can generate millions of candidate molecules for a certain disease, then test their application, significantly speeding up R&D cycles.
"AI automation throughout the drug development pipeline is opening up the possibility of faster, cheaper pharmaceuticals.
"By fully integrating AI into research workflows, biopharma companies can deliver greater patient impact and significant value."