Qontext builds an independent context layer that connects enterprise data sources to AI systems, ensuring company knowledge is current and access-controlled across agents and workflows.
Qontext, based in Berlin, builds an independent context layer designed to allow AI systems within companies to operate using accurate, current organisational knowledge. The company addresses a core challenge in enterprise AI: ensuring that language models, agents, and automated workflows can access relevant information without re-establishing context from scratch for each interaction.
The company's product, Workspace with context base, connects to existing data sources and makes that information available to AI systems via API, MCP, or CLI. Its relational model updates continuously as underlying source data changes, aiming to keep AI outputs aligned with the current state of company knowledge.
Qontext's technical work spans AI context management, data integration, relational modelling, and API/MCP/CLI development. The platform places particular emphasis on control - allowing organisations to specify which context an AI agent may access, manage roles and permissions, and maintain human oversight. Security and compliance form part of the design foundation, with ISO 27001 certification and GDPR-aligned data handling practices.
