Seldon builds a cloud-agnostic machine-learning deployment platform and open source frameworks designed to reduce friction around deploying, explaining and governing ML models in production. The company emphasizes data-centric MLOps, claiming improvements by focusing on production data quality rather than only algorithm changes. Its open source distribution accelerates adoption and allows more efficient delivery of proprietary solutions. Seldon reports a 400% year-over-year growth in its open source frameworks since its November 2020 Series A. Customers named in the article include PayPal, Johnson & Johnson, Audi and Experian. The company has collaborated with Cambridge University and academic ML figures to validate its approach and product. Seldon builds tools to operationalize and deploy machine-learning models, with a focus on eliminating friction between model development and production. Its open-source project, Seldon Core, has supported more than 700,000 models deployed to date and the company says customers see productivity gains up to 92%. Seldon sells an enterprise solution called Seldon Deploy and partners with cloud and platform vendors including Google, Red Hat, IBM and AWS. The startup plans to use new funding to accelerate R&D, drive commercial expansion and take Seldon Deploy to market. It intends to double the size of its team over the next 18 months to support those efforts. The company operates as a cloud-agnostic provider to avoid vendor lock-in and to enable integrations across the ML and DevOps stack. Seldon builds Seldon Core, an open-source machine-learning deployment platform designed to make it easier to manage and optimise ML models at scale. Seldon Core had more than 170,000 installs in 2018. The company plans to release an enterprise-grade product, Seldon Deploy, which will include support for compliance processes, advanced experiments, and model explanations. Seldon is London-based, was founded in 2014, and went through the Techstars Barclays Accelerator in London in 2016. The startup secured a £2.7 million funding round led by Amadeus Capital Partners, with Global Brain Corporation, Techstars and other existing investors participating.

Total raised

$33M

Funding rounds

3

Latest round

Series B

Latest activity

Mar 2023