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Automation & Agents · 2 Nov 2026 · 10:00 CET

Marble Cognition Raises $3.75M Pre-Seed to Build AI Coworkers That Learn by Observing

Unite.AI · 2 Nov 2026 · 10:00 CETRead original at Unite.AI ↗
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Marble Cognition Raises $3.75M Pre-Seed to Build AI Coworkers That Learn by Observing

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The hardest part of automating office work often happens before an AI agent takes its first action: figuring out what employees actually do. A workflow might cross an inbox, a spreadsheet and several business applications, with its exceptions understood by the team but never captured in a formal specification. Marble Cognition has raised $3.75 million in pre-seed funding to turn that operational knowledge into AI coworkers.

Heartcore and Seedcamp co-led the round. Angel participants include a Datadog board member, a Personio founder and executives from McKinsey, Mistral AI and Lovable, according to the announcement. The Munich company will use the financing to scale inference, expand its engineering team and launch in the United States.

Marble’s approach starts with observing work. It captures how processes unfold, turns those observations into structured maps and deploys Marble Coworkers to carry out the resulting workflows in the tools employees already use. People remain involved where judgment or approval is required.

An agent that can navigate software still needs to know which records to consult, what counts as a completed task and when an exception requires escalation. Those instructions are difficult to supply when a company’s real operating procedures exist as habits, informal handoffs and knowledge scattered across its systems.

Marble is betting that this context becomes more valuable as software development and agent-building become easier. Its proposed advantage is an accurate understanding of the work being automated: the sequence of actions, the information used and the decisions that connect one step to another.

The company says its desktop application records screens, clicks and keystrokes within business applications. It uses those observations to build structured process maps that AI systems can interpret, then creates coworkers that execute the process end to end. This connects workflow discovery with deployment, instead of leaving the customer to translate a process analysis into a separate automation project.

“Every company we talk to wants AI to take over real work. But nobody can tell the AI how that work is actually done,” said Felix Rösner, Marble’s co-founder and CEO, in the announcement.

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Unite.AI · 2 Nov 2026 · 10:00 CET

Open the original at Unite.AI ↗