Interloom, a Munich-based enterprise operations platform that captures expert knowledge and transforms it into permanent memory for AI agents, today announced a €14.2 million ($16.5 million) Seed round.
The investment was led by DN Capital, with participation from Bek Ventures and existing investor Air Street Capital.
“AI agents are rapidly moving onto the front lines, but without a company’s specific corporate memory, they will not have the answers or the ability to automate anything,” says Fabian Jakobi, Founder and CEO of Interloom. “We ground their decisions in successful resolutions from the past – ensuring their work is guided by real operational experience and governed through expert oversight – creating a memory that stays with the company forever.”
Recent coverage from EU-Startups highlights several comparable deals across this segment, including happyhotel (Germany, €6.5 million to build AI agents for hotel revenue management), Equixly (Italy, €10 million to scale AI-driven API security testing), Contents (Italy, €5.9 million to expand its AI workflow platform), Rapidata (Switzerland, €7.2 million to scale human feedback infrastructure for AI), Blockbrain (Germany, €17.5 million to advance enterprise-grade AI agents), Elyos AI (UK, €11.1 million to automate field service workflows), Toyo (UK, €3.6 million to develop secure AI agents), and Plato (Germany, €12.2 million to automate sales and ERP workflows).
Together, these rounds amount to approximately €74 million, reflecting steady capital inflows into enterprise AI infrastructure and applications. Germany stands out as a particularly active market, with multiple rounds across the same category, placing Interloom within a concentrated national cluster of enterprise AI development.
Within this landscape, Interloom’s focus on capturing tacit organisational knowledge and converting it into persistent operational memory aligns with a broader move towards improving reliability and context-awareness in enterprise AI deployments.
“Our experience with enterprise AI agents platforms like Cognigy showed us how important context is. An agent is only as good as the specific knowledge it can rely on. The problem is context is dynamic, poorly documented and lives in the daily decisions of expert front-line workers. Interloom stood out by building a corporate context graph that continuously captures real-world decisions and how organisations actually operate,” adds Guy Ward Thomas, Partner, DN Capital.
Founded in 2024, Interloom helps enterprises capture the operational knowledge of their experts and turn it into a memory layer for AI agents. By analysing how real work is performed across systems and teams, the platform builds a corporate memory that enables organisations to automate and continuously improve complex workflows.
While AI agents are advancing rapidly, Interloom believes that enterprises struggle to deploy them in real-world operations because these systems lack a fundamental component: memory of how work is actually done.
Interloom is already solving this for leading enterprises including Zurich Insurance, JLL, and Fiege, processing millions of cases to bridge this “context gap.”
In every company, operational experts solve complex problems because they’ve seen them before. They remember the specific workaround, the internal team that fixed it, and the ultimate resolution. While new employees and AI agents currently rely on formal documentation, the reality is that 70% of operational decisions are never written down – according to Interloom.
This critical experience remains locked in the minds of employees, hidden across millions of emails, tickets, and call transcripts.
Interloom aims to provide the missing memory layer. When complex issues escalate to Interloom, operational experts resolve them alongside AI. Once an expert resolves a case, Interloom ensures that future employees and AI agents have access to that memory.
Each resolution becomes part of Interloom’s Context Graph – a continuously evolving model of operational decisions.
Much like how Google Maps improves routes based on real-time traffic patterns, Interloom’s memory grounds the actions of expert teams and AI agents, enabling the automation of complex workflows based on real-world experience rather than static manuals.
Interloom is already processing millions of operational cases, positioning itself as the next-generation platform for business automation that learns from how operational work actually flows.
Read the orginal article: https://www.eu-startups.com/2026/03/german-startup-interloom-lands-e14-2-million-seed-funding-for-ai-agent-knowledge-infrastructure/
