The Munich-based startup Interloom has secured $16.5 million in funding.

      The startup based in Munich is developing what it refers to as a ‘context graph’, an ever-evolving representation of how operational decisions are made within a company, derived from millions of real-world cases rather than from documents that might never have been created.

      In every deployment of AI within an organization, there is a common point of friction that individuals often encounter early on. The AI agent may possess technical abilities. It can read documentation, follow instructions, and perform tasks. However, it struggles to replicate the intuition of a person who has spent fifteen years on the job and understands, from experience, why the standard procedures fail on Tuesdays in the logistics department. This critical knowledge has never been documented because there was no need to write it down until now.

      This is the challenge Interloom is aiming to address. The Munich-based startup, which operates in Munich, Berlin, and London, announced on March 19 that it has secured $16.5 million in a seed funding round led by DN Capital, with contributions from Bek Ventures and existing investor Air Street Capital.

      The funding round marks a substantial increase from the company’s initial $3 million seed round led by Air Street in March 2024 when the startup first emerged from stealth mode.

      Interloom’s primary offering is known as the Context Graph: a constantly updating model that tracks how operational decisions are actually made within an organization, created by analyzing millions of real examples, support emails, service tickets, call transcripts, and work orders, while identifying patterns in how expert employees resolve issues.

      Founder and CEO Fabian Jakobi describes the challenge in terms of tacit knowledge, a term introduced by British-Hungarian philosopher Michael Polanyi, which suggests that most expertise cannot be fully expressed by the individual who possesses it. Jakobi estimates that about 70% of operational decisions are never formally recorded.

      He draws an analogy to Google Maps: similar to how the navigation tool learns the best routes from live traffic data, Interloom crafts a map of the ways operational experts navigate to solve issues, using that map to assist AI agents and new hires encountering similar challenges. The system is continuously updated, ensuring that every solved case contributes to the organization's collective knowledge rather than being lost when the employee who addressed it leaves or retires.

      This retirement risk is part of the startup's pitch. The press release mentions that around 10,000 baby boomers are exiting the US workforce each day, a statistic extensively documented by Pew Research.

      The assertion is that businesses are confronting a growing issue: decades' worth of institutional knowledge is being lost at a critical time when AI is expected to automate complex operational tasks. Without first capturing that knowledge, the AI lacks valuable data to rely on.

      Interloom's initial clients include Zurich Insurance, JLL, and logistics firm Fiege, as well as Commerzbank and Volkswagen, with the latter two independently confirmed by Fortune in its exclusive report on the funding. At Commerzbank, Interloom analyzed millions of customer support emails in comparison with internal records and reportedly narrowed the discrepancy between documented procedures and actual work practices from about 50% to 5%.

      At Zurich Insurance, the company successfully participated in an internal AI competition, competing with what Jakobi described to Fortune as 2,000 AI-native startups for an underwriting case.

      The list of investors provides its own logic supporting this thesis. Guy Ward Thomas, the DN Capital partner leading the investment, previously served as the first institutional investor in Cognigy, a German enterprise conversational AI platform, which DN Capital supported from its Series A in 2019 and was acquired by NICE in August 2025 for $955 million—considered Europe’s largest AI exit at that time.

      Ward Thomas emphasized that the key takeaway from that investment was the importance of organization-specific context in making AI agents function effectively in real-world scenarios. Mehmet Atici, who oversees Bek Ventures' involvement, was an early supporter of UiPath, a pioneer in robotic process automation that went public in New York in 2021. He argues that the current surge in AI agent adoption signifies the next significant shift in enterprise automation following RPA.