Interloom builds a continuously evolving “context graph” that stores decisions and outcomes from past work, enabling AI agents and employees to reference prior resolutions. The platform captures tacit operational knowledge from real-world workflows to reduce knowledge loss from workforce changes. Interloom positions this persistent memory layer as a way to give AI agents company-specific context and improve automation of complex processes. Founder and CEO Fabian Jakobi emphasizes grounding AI decisions in successful past resolutions with expert oversight. The company recently raised $16.5 million in a seed round to further develop the platform, enhance its AI memory capabilities, and expand its enterprise automation offerings. No revenue, user metrics, founding year, or location were disclosed in the article.

Total raised

$20M

Funding rounds

2

Latest round

Seed

Latest activity

Mar 2026