Biographica raises £7m to accelerate AI-driven crop trait discovery

Biographica, a London-based startup applying artificial intelligence to crop genetics, has raised £7 million ($9.5 million) in a seed funding round to speed the discovery of traits such as drought tolerance, disease resistance and nutritional quality.

The round was led by Faber VC, with participation from SuperSeed, Cardumen Capital, The Helm, EQT Foundation, Sie Ventures, and existing investors including Chalfen Ventures and Entrepreneurs First. The funds will be used to expand proprietary data collection, extend its AI platform to additional crop traits, and deepen partnerships with seed companies.

Alongside the financing, Biographica announced a new collaboration with BASF’s vegetable seeds business, Nunhems. The company did not disclose details but said the partnership builds on pilot projects completed over the past two years with seed and precision-breeding companies, including two of the five largest global seed firms.

Founded in 2022 by chief executive Cecily Price and chief technology officer Dominic Hall, PhD, Biographica aims to address a major bottleneck in crop development: identifying which genes control economically important traits. While tools such as CRISPR allow precise gene editing, determining which genes to target remains slow and costly.

“Current pipelines rely on literature, statistical studies, and high-throughput testing,” said Price. “These methods deliver low success rates and force companies to test thousands of edits to find one that works, while overlooking many novel genes.”

Biographica’s platform applies multi-modal machine learning to genomic, structural and physiological data to predict which genes are most likely to influence traits and how to edit them with minimal unintended effects. In pilot projects, the company said it identified validated gene targets faster than traditional methods and uncovered novel targets that conventional approaches missed.

The platform combines computational predictions with rapid experimental validation in a “lab-in-the-loop” model, a concept drawn from drug discovery, where results feed back into the AI to improve accuracy over time.

Many firms still rely on genome-wide association studies and quantitative trait loci mapping, which link DNA variants to traits through statistical correlation rather than direct causation, Hall said. Biographica’s models aim to go further, predicting causal gene-trait relationships and ranking targets for editing.

The company’s models are trained on public genomic datasets and refined using data generated in-house. This allows it to work with partners without requiring their proprietary data at the outset, addressing concerns about sharing sensitive information.

Commercial validation has been central to attracting investors. Biographica has partnerships with Cibus, focused on disease resistance in oilseed rape and canola, and other seed companies. Some newly identified gene targets are already progressing into downstream research pipelines, the company said.

Unlike many in-house AI systems, Biographica’s platform is crop- and trait-agnostic, with applications across vegetables, oilseeds, and major cereals. The company said it will use the funding to scale operations and accelerate the deployment of AI-driven crop improvement as climate change increases pressure on agricultural systems.