4 billion years of protein evolution

We help R&D teams discover and design protein products that nobody else can. Together we can create better food, better medicines and better products for the planet.
Understanding nature with AI

Discover and design proteins using nature's hidden rules

We partner with R&D scientists 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 largest in existence.

Work with us to tap into 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.
Talk to us about ABS
Meet the team

We believe in the power of biology to change the world

We are Antarctic ice-divers and graph ML scientists. We'd love to meet you.
Biology meets cutting-edge data science

Capturing complex function in silico

Our sampling partnerships give you access to entirely new genetic biodiversity. For every metagenomic sample we take, we capture thousands of environmental, functional, and other datapoints.

This gives us the ability to computationally predict how proteins perform in the real world, like never before.
How it works
Our news

The latest from Basecamp Research

A day in the life of: a metagenomics bioinformatician in a biotech start-up
Marcus Leung reveals what life is like at the crossroads between industry and research as a bioinformatician for Basecamp Research.
AI-enhanced protein design makes proteins that have never existed
Nature Biotechnology News reflects on how protein engineers are drawing on rapidly evolving tools and datasets to pursue more sophisticated de novo protein designs.
ZymCTRL: a conditional language model for the controllable generation of artificial enzymes
Pre-print from our first collaboration with Dr Noelia Ferruz on an enzyme-specific language model to provide new opportunities to design purpose-built artificial enzymes.