How This AI Startup Just Raised $16.5M to Solve the 'Tacit Knowledge' Crisis in Enterprises

Tacit knowledge—the unspoken expertise that experts carry but can't fully articulate—is a major bottleneck for AI agents in large enterprises. According to Interloom's CEO, up to 70% of operational decisions are undocumented, making automation challenging.

Interloom, a Munich-based startup, has raised $16.5 million in venture capital to tackle this issue. The funding round was led by DN Capital, with participation from Bek Ventures and existing investor Air Street Capital. This follows a $3 million seed round announced in March 2024, though the company's valuation remains undisclosed.

The Problem: AI Agents Lack Corporate Memory

Fabian Jakobi, Interloom's founder and CEO, explains that when a complex support ticket arrives, veteran staffers know the workarounds and resolutions from experience, not manuals. "The most important person at the bank is the person who knows whether the documentation is right or not," Jakobi told Fortune. "They're often the lowest paid. But they determine quality."

Interloom's Solution: Building a 'Context Graph'

Interloom's approach involves ingesting millions of operational records—such as support emails, service tickets, and call transcripts—to create a 'context graph'. This continuously updated map shows how problems are actually resolved within an organization, similar to how Google Maps learns optimal routes from traffic data. It guides AI agents and new employees by mapping the paths experts take.

Real-World Applications and Success Stories

Interloom's software is already live with several large European enterprises:

• At Commerzbank, it analyzed millions of customer support emails and reduced the gap between documented and actual operational knowledge from about 50% to 5%.
• At Volkswagen, it processes customer support tickets.
• At Zurich Insurance, Interloom won a company-wide AI competition for an underwriting use case, beating out 2,000 other AI-native startups.

Jakobi emphasizes that underwriting decisions reflect a company's specific risk appetite and institutional knowledge, which general-purpose AI models lack. "The Zurich underwriter knows how their broker chat underwriting works much better than Accenture does," he said, targeting large consulting firms.

Investor Confidence and Market Timing

Investors back Interloom's thesis. Guy Ward Thomas of DN Capital stated, "an agent is only as good as the expert decisions it can rely on." Mehmet Atici of Bek Ventures, who previously backed UiPath, noted that AI is unlocking a new wave of enterprise automation adoption.

Timing is key: the 'Great Retirement' sees about 10,000 Baby Boomers retiring daily in the U.S., taking decades of institutional knowledge with them—just as companies scale AI deployment.

Competitive Landscape and Future Plans

Jakobi sees inertia as the biggest rival, with enterprises assuming operations will continue unchanged. Interloom's next product is a 'Chief of Staff' layer for real-time visibility into AI agent performance, including version control for processes.

While companies like OpenAI, ServiceNow, and Microsoft work on similar AI agent management layers, Jakobi believes Interloom's context graph provides a distinct advantage by offering insight across entire complex processes.