London’s Encord raises €50 million for physical AI push
London-based startup Encord has secured a €50 million funding round to drive the next phase of physical AI deployment, underscoring growing investor confidence in AI systems that interact directly with the real world. The fresh capital will be used to expand its data-centric AI platform, enhance product development and deepen its presence across key sectors including robotics, healthcare and industrial automation.
Building the infrastructure for real-world AI
Encord specializes in tools that help teams build, train and validate AI models that must perform reliably in physical environments – from factory floors and hospitals to autonomous machines. Its platform focuses on high-quality data annotation, model evaluation and continuous monitoring, enabling customers to reduce failure rates and improve safety as systems move from lab prototypes to live deployment.
By providing workflows tailored to vision-based and sensor-based AI systems, Encord aims to solve one of the biggest bottlenecks in the industry: turning experimental models into robust, production-grade solutions that can be trusted in mission-critical settings.
Scaling across sectors and geographies
The new funding will allow Encord to grow its engineering and product teams in London and other hubs, while investing in sector-specific capabilities for regulated industries. In healthcare, this includes support for medical imaging AI and compliance-ready workflows. In manufacturing and logistics, the company is targeting customers that rely on computer vision to power quality control, robotics and safety monitoring.
With demand rising for dependable AI infrastructure, the company is positioning itself as a foundational layer for organisations seeking to deploy physical AI at scale, while maintaining rigorous standards for reliability, transparency and governance.
Rising competition in AI tooling
The funding round places Encord among a growing cohort of European startups building specialised AI development platforms. As enterprises move beyond experimentation, competition is intensifying around tools that can shorten deployment cycles and reduce operational risk. By focusing squarely on the challenges of physical AI, Encord is betting that safety, data quality and real-world performance will be the decisive factors in the next wave of AI adoption.