Qontext, a Berlin-based startup, has announced the closing of a $2.7 million pre-seed funding round. The company focuses on developing an independent context layer for artificial intelligence systems.

Funding Details

The round was led by HV Capital, with participation from Zero Prime Ventures and a group of founders and operators from the AI infrastructure, automation, and enterprise software sectors, including Jan Oberhauser (n8n), Emil Eifrem (neo4j), Bastian Nominacher (Celonis), Philipp Heltewig (Cognigy), and Fabian Veit (make.com).

Qontext's Solution

Founded in 2025 by Lorenz Hieber and Nikita Kowalski, Qontext aims to provide AI systems in production with relevant, up-to-date context. The platform is used by fast-growing startups and larger enterprises deploying AI across functions such as marketing, sales, and customer support. The goal is to improve the number of processes that can be reliably automated.

The Challenge of Context in AI

Despite rapid advances in AI capabilities, many organizations struggle to achieve consistent outcomes and measurable returns. This is often due not to model quality, but to the absence of a reliable foundation of contextual information covering customers, products, processes, and internal policies. Such data is typically fragmented across systems and teams, frequently changing and sometimes inconsistent, which limits the scalability and reliability of AI applications.

Future Prospects

With the new funding, Qontext plans to expand its platform and team to develop reusable context infrastructure, enabling AI processes to operate on reliable and continuously updated context across applications and use cases.