OctaiPipe, an end-to-end Edge AI platform, has raised £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 federated learning technology and scale availability of its platform for Internet of Things-dependent critical industries including energy, utilities, telecoms, manufacturing and connected device OEMs.

OctaiPipe has developed a new decentralised approach to training AI models which does not require the exchange of data between IoT devices and cloud servers. 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.

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.

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Arnaud Lagarde has also been appointed as chief revenue officer. 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 a multi-trillion dollar industry,” said Mads Jensen, managing partner at SuperSeed. “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.”

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.”

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