BERLIN / LONDON (IT BOLTWISE) – Octonomy AI GmbH has successfully secured $20 million in a seed funding round to further develop its AI platform for heavy industry companies. The platform promises to automate the data verification process and increase troubleshooting efficiency.
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Octonomy AI GmbH, a startup specializing in artificial intelligence, recently closed $20 million in seed financing. This investment is led by Macquarie Capital Venture Capital and supported by other investors including Germany’s NRW.Bank, TechVision Fund and Capnamic. The latter had already led a financing round of $5 million for Octonomy in January.
Octonomy’s platform aims to automate the often fragmented data verification process in heavy industry. Engineers involved in troubleshooting machines often need to access various systems to obtain technical data such as schematics and error logs. Octonomy promises to simplify this process by using AI agents that can answer technical questions about industrial equipment with over 95% accuracy.
Another advantage of the platform is its easy implementation. Companies do not need to manually load technical documents into the software as Octonomy directly accesses enterprise resource planning and other internal applications. The data is brought together in a central repository, normalized and divided into smaller, efficiently processable files.
The platform uses three types of agents to respond to user requests: support agents for simple requests, advisory agents for more complex tasks, and a supervisor agent that analyzes the requests and selects the most appropriate agent. According to Octonomy co-founder and CEO Sushel Bijganath, the platform enables over 95% response quality, well above the usual 50% offered by standard AI platforms.
With the backing of Macquarie Capital Venture Capital, Octonomy plans to make its platform more widely available in both Europe and the US. This expansion could fundamentally change the way heavy industry companies handle technical data and significantly improve the efficiency and accuracy of troubleshooting.
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