Berlin-based Qontext has raised $2.7M in a pre-seed funding round to accelerate the development of its independent context layer for artificial intelligence.
The round was led by HV Capital, with participation from Zero Prime Ventures and a group of angel investors including Jan Oberhauser (n8n), Emil Eifrem (Neo4j), and Bastian Nominacher (Celonis).
Decoupling business context from AI models
Founded in 2025, Qontext is building a foundational infrastructure layer that separates business context such as product data, policies, customer history, and internal knowledge from AI models and applications. The goal is to give organisations a single, reusable source of truth that can be accessed consistently by all AI agents and automated workflows.
Led by CEO Lorenz Hieber and CTO Nikita Kowalski, the company positions its platform as a missing layer in modern AI stacks, allowing teams to manage context independently of individual models, tools, or vendors.
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One context base for all AI-driven workflows
Qontext ingests and unifies data from CRMs, documents, emails, chat tools, and other internal systems. By centralising this information and adding governance and control mechanisms, the platform enables companies to scale AI use cases across departments without duplicating logic or fragmenting data.
The solution is currently used by high-growth startups and large enterprises, with an initial focus on marketing, sales, and customer support teams.
Next steps after the pre-seed round
The newly raised capital will be used to deepen the platform’s capabilities and grow the team, with a focus on building robust, reusable context infrastructure that can support multiple AI agents and enterprise workflows.
About Qontext
Qontext builds an independent context layer for AI, turning company knowledge into reusable intellectual property. By providing a unified, governed context base, the platform enables organisations to scale AI reliably across teams and functions while ensuring consistent, efficient, and controlled use of business data.
