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We're building an integrated ecosystem for AI-powered biology

Biohub's platform accelerates the development and application of state-of-the-art AIxBio models. We help developers build biologically impactful models faster, and empower biologists to use them with ease — creating a cycle of collaboration that drives AI-powered biological discovery forward.

Feedback loop diagram

Diagram showing a feedback loop between data, models, benchmarks, and workflows connecting biologists and ML developers.

[ For developers ]

A developer toolkit to build faster for scientific impact

Access multimodal, ML-ready data to fuel your model development

  • Access thousands of high-quality datasets from CELLxGENE, CryoET data portal, and more in one unified place
  • All data is standardized to a cross-modality metadata schema for consistent querying
  • Efficient access options through API and CLI
Command-line search showing transcriptomic dataset metadata and organism stats with visual organism summary.

Understand where you can make the biggest impact with biologist-defined benchmarks

  • Use biologist-defined tasks, metrics, and datasets to evaluate model performance
  • Identify gaps where your model can make a difference
  • Evaluate performance as you build with pre-built benchmarking packages
Benchmark leaderboard and CLI table showing model rankings and dataset-task mappings for biological data analysis.

Build and share your model faster with a single, powerful CLI

  • Speed up cycles of model development and evaluation with programmatic access to data, model, and benchmarking commands
  • Contribute to the scientific community and submit your model for others to explore.
Model packaging workflow showing completed steps and staging issue in CLI, with model descriptions listed alongside.

[ For biologists ]

An AI Workspace to supercharge your research pipelines

Compare models using biologically relevant benchmarks to confidently choose the best one for your research needs

  • Our benchmarks are standardized, reproducible, and community-driven, prioritizing performance on biologically relevant tasks over standard model performance metrics.
  • We’re starting with single-cell analysis tasks and expanding to more domains.
Model ranking table with cell type classification scores and heatmap comparing performance across datasets and metrics.

Run models on your data with flexible no-code or low-code options. Inference included.

  • Each model comes with a vetted quickstart notebook
  • Try the beta version of our interactive, no-code tools for single cell embedding and analysis
  • Upload your own data to run with models to generate embeddings, and use interactive visualizations to analyze the results.
UMAP visualization of single-cell data with model selection and cell type filtering panel showing color-coded clusters by category.

Explore newly-added models

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Our approach

At Biohub, we’re building the technology to help scientists around the world use AI-powered biology to dramatically improve the ability to understand and manage disease.

Our strategy is to create a flywheel for scientific discovery. We do this by building new technologies, generating biological datasets, developing new AI models, and conducting frontier research that work together to engineer novel biological systems. This virtuous cycle opens entirely new and more effective pathways for understanding and advancing human health.

Learn more about our approach|