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London-based Twig raises £3M to identify sustainable ingredients with AI and robotics

Twig founders
Picture credits: Twig

London-headquartered bioengineering startup Twig has just emerged from stealth mode and raised £3 million in funding. The investment came from Project A, Seedcamp (which backed Antavo and Lindus Health), Zero Carbon Capital, UKI2S, Gaingels, and angels via HackCapital.

“Many of the biggest little ingredients that go into the products we use in our daily lives are hugely damaging for the planet,” said CEO and co-founder of Twig,  Dr Russ Tucker, who also founded Ivy Farm Technologies. “Twig is bioengineering better – through the right combination of AI and automation, we can deliver a step-change in bioengineering, driving a global transition from unsustainably resourced ingredients to bio-fermented ingredients in a way that benefits everyone – people, producers, and the planet.” 

Oliver Sexton, investor at UKI2S, said: “Twig is using biology to make a vast array of products using entirely sustainable alternatives to petrochemicals. Its focus on moving manufacturing to a low-impact footing is core to our planet’s healthy future.”

Deploys AI and robotics to test alternatives

Many of the little ingredients that go into the products we use in our daily lives are hugely damaging for the planet. This needs to change, and it should happen at a faster pace.

Founded by James Allen, Satnam Surae, and Russ Tucker in late 2022, Twig uses AI and robotics to create sustainable ingredients that don’t cost the earth. The company’s mission is to drive a global transition away from unsustainably resourced ingredients to bio-fermented ingredients such that it benefits everyone from people, producers, and the planet. 

With AI and robotics, the company identifies eco-friendly substitutes for substances such as palmitic acid, isoprene, and acetone. Twig’s biotech process consists of three core components – a bio tool that creates the base ingredients; robots that handle and analyse the bacteria; and AI that combines the information gathered from the bio tool and robots to optimise the process and suggest refinements for higher-quality outcomes.

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