Interloom raises $16.5M to build an operational knowledge "memory" for enterprise AI agents

Munich-based Interloom has raised $16.5 million in seed funding to further develop its platform, which helps enterprises build a persistent "memory" layer for AI agents made out of operational knowledge that is seldom documented through traditional means. The round was led by DN Capital, with participation from Bek Ventures and existing investor Air Street Capital.

While AI agents are rapidly advancing, they struggle in real-world enterprise settings because they lack context on how work is actually performed. Interloom addresses this by capturing the undocumented expertise that drives many, if not most, of a company's operational decisions. Interloom says its platform aims to capture the knowledge that often remains locked in employees' minds, or at best, scattered across emails, tickets, and call transcripts.

The platform works by having operational experts resolve complex cases alongside AI. Each resolution becomes part of Interloom's "Context Graph," a continuously evolving model of operational decisions that provides permanent memory for both future employees and AI agents to reference. Thus, in addition to providing AI agents with much-needed context, Interloom's "Context Graph" ensures continuity and consistency in operational decisions among employees, a mission that has become of greater importance as more and more people belonging to older generations retire from the workforce.

"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," said founder and CEO Fabian Jakobi.

Interloom already serves major enterprises including Zurich Insurance, JLL, and Fiege, processing millions of operational cases. The company will use the funding to expand its platform and capabilities in enterprise AI automation.