Interloom, an enterprise operations
platform that captures expert knowledge and converts it into a persistent
memory layer for AI agents, has closed a $16.5 million seed funding round. The
round was led by DN Capital, with participation from Bek Ventures and existing
investor Air Street Capital.
The company addresses a key limitation
in enterprise AI adoption: the lack of operational context. While AI agents can
process information, much of how work is actually performed remains
undocumented. Interloom’s platform captures this knowledge from real-world
workflows, enabling both employees and AI systems to access past resolutions
and apply them to new cases.
Fabian Jakobi, founder and CEO of
Interloom, said that as AI agents move into operational roles, their
effectiveness is limited without access to company-specific knowledge, reducing
their ability to provide accurate responses or enable automation.
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.
Jakobi added.
Interloom builds a continuously
evolving “context graph” that stores decisions and outcomes from past work.
This allows AI agents to operate based on accumulated experience rather than
static documentation, supporting more effective automation of complex
processes. The platform also addresses knowledge loss driven by workforce
changes by preserving expertise within the organisation.
With the new funding, Interloom plans
to further develop its platform and expand its capabilities in enterprise AI
and workflow automation.