Energy Startup Invertix Raises €1.7 Million for AI Operations Platform
Invertix has closed a €1.7 million pre-seed round to build infrastructure that lets energy companies deploy AI agents across their operations. The Munich-based startup said it has already reached multiple six figures in annual recurring revenue less than a month after securing the funding.
Co-founders Joseph Perrotta and Kaan Durmaz started the company in early 2025 after working together at Brightdale. They spent months prototyping AI products before committing full-time and relocating to Munich to work out of the TUM.ai office. Menelaos Panagiotis Fotiadis and Nicole Thorisch later joined the founding team.
How the founders identified the opportunity
The team conducted extensive market research to pick their initial focus. They contacted more than 5,000 people in the energy sector and held conversations with over 500 energy professionals - operators, founders, investors, engineers, and executives.
Through those discussions, they identified operational problems they believed AI could address. The founders viewed energy as foundational to broader economic and technological progress, making it a natural area to build long-term solutions.
What Invertix is building
The company describes its product as an AI operating layer for energy companies. According to Perrotta, the infrastructure "allows energy companies to deploy AI agents inside their organizations and 10x their daily operations."
The platform targets the operational workflows specific to energy firms, rather than selling generic AI tools. This focused approach reflects what the founders learned during their market validation phase.
Backing and next steps
Investors in the round include Felix Krause of Vireo Ventures and Irene of Italian Founders Fund, along with a network of angel investors who helped refine the company's strategy during early development.
Invertix plans to accelerate product development and expand its commercial operations with the new capital. The startup's early revenue suggests the market is receptive to AI-driven solutions for energy operations.
For operations managers in the energy sector, understanding how AI agents and automation can improve efficiency is increasingly relevant. Those seeking a structured approach to this shift may find value in an AI learning path for operations managers.
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