This investment will enable OctaiPipe to enhance its pioneering Federated Learning technology and expand the reach of its platform across vital Internet of Things (IoT) reliant sectors such as Energy, Utilities, Telecoms, Manufacturing, and connected device Original Equipment Manufacturers (OEMs).

Additionally, OctaiPipe announced the appointment of Arnaud Lagarde as its Chief Revenue Officer. Mr. Lagarde, previously the Vice President of Sales at Humanising Autonomy, brings extensive experience in global sales and market entry strategies, particularly in the Automotive, Autonomous Vehicles, and smart city solutions domains.

Critical Infrastructure, characterised by data-intensive and high-stakes environments, prioritises data security. AI's integration with IoT in these sectors holds immense potential for boosting productivity, enhancing sustainability, and monitoring asset health. In the UK energy sector alone, full exploitation of AI could lead to a reduction in energy system costs of up to £70 billion by 2050, as per the UK government's digitisation strategy. However, the use of connected devices and AI in these sectors has been restrained due to data security concerns and escalating Cloud AI costs.

OctaiPipe's Federated Learning technology presents a revolutionary decentralised method for training AI models that negates the need for data exchange between IoT devices and Cloud servers. By locally training AI models at the Edge with IoT device data, it significantly improves performance and system resilience, bolsters data security, and drastically cuts Cloud data expenses.

Established in 2022, OctaiPipe's end-to-end Federated Learning Operations (FL-Ops) platform is tailor-made for data scientists and AI engineers in Critical Infrastructure. It facilitates easy deployment and automation of AI at the Edge, and the orchestration and management of distributed machine learning across extensive networks of smart IoT devices. Available as a Platform-as-a-Service (PaaS) on Microsoft Azure, AWS, or Private Cloud, OctaiPipe is currently in use by over 20 customers and device OEMs.

Mads Jensen, Managing Partner at SuperSeed said: “Critical Infrastructure is a multi-trillion dollar industry. Across Energy, Utilities and Telecoms - on-device Federated Learning has the potential to improve performance, reduce failures, enhance security and lead to more efficient, more sustainable services. The OctaiPipe team has already demonstrated significant customer traction and we are delighted to support them as they scale to address this important market.”

Dr Will Cavendish, Global Digital Services Leader at ARUP, said: “Water treatment is a complex environment that is expensive for water companies to operate and carries significant regulatory risk, including heavy fines for incorrect treatment. Federated Learning – including solutions such as OctaPipe’s – is an AI technology that can help. It allows continuous learning from multiple and dispersed local data sources, better predicting future challenges. As data from the built environment scales, centralised solutions start to become unmanageable and uneconomic. So Federated Learning reduces cost and cloud dependence, while maintaining model accuracy, security and privacy. Federated Learning also improves system resiliency - meaning there is no downtime risk and systems can remain fully operational in the event of an outage or failure.”

Miles Kirby, CEO of ARM-backed Deeptech Labs said: “At Deeptech Labs, we look for founders addressing global challenges with ground-breaking technology. Eric and the OctaiPipe team are world-leading pioneers of Federated Learning and Edge compute. By applying this technology to Critical Infrastructure as an easy-to-use Platform-as-a-Service, OctaiPipe is helping ensure the services and utilities the world relies on can benefit from the latest advances in AI without incurring the costs and risks of running models on the Cloud.”

Eric Topham, CEO and Co-Founder of OctaiPipe said: “The world depends on Critical Infrastructure not to fail but, more than that, to continually improve performance, remain secure and continually become more efficient and sustainable. It’s clear that AI has the potential to unlock massive gains in Critical Infrastructure, but only if we can trust that its critical data is secure. With OctaiPipe, data scientists working in sectors such as Energy, Utilities, Telecoms and Security can for the first time use a secure end-to-end platform to design, deploy and manage Federated Learning locally across Edge device networks and at scale. This £3.5 million in funding will enable us to continue advancing our proprietary technology and scale our operations to address this trillion-dollar market so that the infrastructure we all rely on is smarter, more sustainable and secure.”