LONDON--(BUSINESS WIRE)--OctaiPipe, the end-to-end Edge AI platform, has announced raising £3 million in pre-Series A funding and a £500,000 non-equity grant. The pre-Series A round was led by SuperSeed with Forward Partners, D2, Atlas Ventures, Martlet Capital, Gelecek Etki VC and Arm-backed Deeptech Labs also participating.
The money will allow OctaiPipe to further develop its proprietary Federated Learning technology and scale availability of the OctaiPipe platform for Internet of Things (IoT) dependent critical industries including Energy, Utilities, Telecoms, Manufacturing and connected device OEMs.
In addition to the funding, OctaiPipe has also announced the appointment of Arnaud Lagarde as Chief Revenue Officer. Mr. Lagarde will lead OctaiPipe’s commercial development. Prior to joining OctaiPipe, Mr Lagarde was the Vice President of Sales at Humanising Autonomy where he led the global sales efforts and go-to-market initiatives across Automotive, Autonomous Vehicles and smart city solution providers.
Critical Infrastructure is typified by data-rich, highly demanding environments where data security is often paramount. The application of AI on data collected by IoT devices has tremendous potential in Critical Infrastructure to increase productivity, improve sustainability and monitor asset health and performance. In the UK’s energy sector alone, the UK government’s digitisation strategy estimates AI, if fully harnessed, could reduce energy system costs by up to £70 billion by 2050. However, due to security concerns regarding data processing in the Cloud and rising Cloud AI costs, the utilisation of connected devices and AI in Critical Infrastructure has, until now, been limited.
OctaiPipe Federated Learning is a new decentralised approach to training AI models which does not require the exchange of data between IoT devices and Cloud servers. In Federated Learning, the data on IoT devices is used to train the AI model locally at the Edge, maximising performance and system resilience, increasing data security and radically reducing Cloud data costs.
To watch an explainer of Federated Learning, click here.
Launched in 2022, OctaiPipe provides data scientists and AI engineers working in Critical Infrastructure with a trustworthy end-to-end Federated Learning Operations (FL-Ops) platform. The OctaiPipe platform enables users to easily deploy and automate AI to the Edge, and orchestrate and manage distributed machine learning across scalable networks of intelligent IoT devices. Available as a Microsoft Azure, AWS or Private Cloud Platform-as-a-Service (PaaS), the OctaiPipe platform is currently in deployment with 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 OctaiPipe’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.”
About OctaiPipe:
OctaiPipe is a end-to-end Edge AI platform optimised for creating, deploying, and managing machine learning solutions in critical infrastructure environments. Deployments on OctaiPipe are more affordable, secure, scalable, and resilient for on-device intelligence due to its advanced on-device Federated Learning capabilities, as well as innovative edge MLOps technology.
With its cost-efficient, accelerated and federated AI, OctaiPipe is removing the common barriers to market while maximising security and privacy, and minimising Cloud dependency and Cloud costs. OctaiPipe is headquartered in London, UK and is funded by a portfolio of investors including SuperSeed, Forward Partners, D2, Atlas Ventures, Growceanu Angel Investment, Kinled Holding, Martlet Capital, Gelecek Etki VC and Arm-backed Deeptech Labs
