Qontext, a Berlin-based startup building an independent context layer for AI, has raised $2.7 million in pre-seed funding to help companies run AI workflows, agents, and applications on a shared, reusable base of governed, continuously updated business context. The round was led by HV Capital, with participation from Zero Prime Ventures, and included a group of AI and enterprise software founders and operators.
The company positions “context,” not model capability, as the limiting factor for consistent AI outcomes inside organizations. Qontext argues that critical knowledge about customers, products, processes, and policies is typically scattered across tools, changes frequently, and often exists in conflicting versions, producing generic outputs that struggle to scale beyond isolated pilots.
Founded in 2025 by Lorenz Hieber and Nikita Kowalski, Qontext says its platform is already being used in production across teams, including marketing, sales, and support, and that a centralized context foundation can increase the number of processes that can be reliably automated with AI. The company’s approach is to maintain context once and deliver the right information at runtime across different AI experiences, while preserving governance and control over what information flows into which process.
HV Capital led the round, with Zero Prime Ventures participating. The angel group includes Jan Oberhauser (n8n), Emil Eifrem (neo4j), Bastian Nominacher (Celonis), Philipp Heltewig (Cognigy), and Fabian Veit (make.com), among others. Qontext said it will use the new capital to expand its platform and team to build reusable context infrastructure that remains trusted and continuously updated across applications and use cases.
KEY QUOTES:
“Putting a great model into an organization without context is like expecting a world-class hire to deliver on day one without any onboarding – the capabilities are there, but the results won’t be. With Qontext, companies can roll out new AI tools and agents that are fully context-aware from day one.”
Lorenz Hieber, Co-Founder & CEO, Qontext
“Context fragmentation is one of the toughest infrastructure problems in AI today, and Qontext is solving it at scale.”
Jan Oberhauser, Founder & CEO, n8n; Angel Investor
“What convinced us is that Qontext is not another AI feature, but a foundational layer every serious AI stack will need.”
Ann-Christin Stiehl, Investor, HV Capital
“We’re dealing with millions of data points, constantly changing information, and complex access controls across humans and agents. But solving this is also the biggest lever for making AI work at scale.”
Nikita Kowalski, Co-Founder & CTO, Qontext
