Nature-inspired biodesign


We leverage our unprecedented knowledge of the natural world to create better medicines, better food and better products for the planet.
Understanding nature with AI

Discover and design proteins using nature's hidden rules

We partner with R&D teams to develop proteins that meet their most challenging requirements in applications as broad as food, pharma, and bioremediation.

Having sampled from most extreme and extraordinary biomes on the planet, our knowledge graph of natural biodiversity is the most comprehensive and diverse in existence. This data advantage allows us to rapidly develop AI that outperforms state-of-the art.

Work with us to tap into our never before seen protein sequences, natural or generated by our proprietary machine learning methods.
How we work
Equitable benefit sharing

Supporting and valuing global biodiversity

We are on a mission to to make protecting and restoring biodiversity economically attractive in alignment with the Nagoya Protocol's Access and Benefit Sharing principles, as part of the United Nation's Convention on Biological Diversity.

We’ve already teamed up with on-the-ground partners in 5 continents, from national parks to farm owners, and we're continuing to reach out to new partners to expand our model for long-term biodiversity protection.
Learn more about ABS
Join our team

We believe in the power of biology to change the world

We are polar explorers, graph ML scientists, policy experts and much more.
Our news

The latest from Basecamp Research

Basecamp Research Launches BaseFold: A Breakthrough in 3D Protein Structure Prediction of Large, Complex Protein Structures
BaseFold leverages Basecamp Research's purpose-built foundational dataset to significantly increase prediction accuracy of large, complex protein structures and small molecule interactions — it is up to six times more accurate than AlphaFold2 and offers up to a three-fold improvement in small molecule docking.
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Improving AlphaFold2 Performance with a Global Metagenomic & Biological Data Supply Chain
With higher protein sequence diversity captured in this dataset compared to existing public data, we apply this data advantage to the protein folding problem by MSA supplementation during inference of AlphaFold2.
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Why we’re so excited about the Arc Institute’s new Evo model
At Basecamp Research, we’re on a mission to build the perfect foundational datasets for AI in biology. Now, finally, it feels like the model architectures are beginning to get sophisticated enough to unlock the true potential of what we’ve built.
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