Marble Cognition raises $3.75M for workflow-capturing AI agents
Munich startup Marble Cognition launched its Coworkers AI agents alongside a $3.75 million pre-seed round led by Heartcore and Seedcamp, according to SiliconANGLE AI. Its desktop app captures employee screenshots, clicks, and keystrokes, then converts them into structured process maps that agents can execute across existing software stacks. Marble says recorded data is anonymized and can remain in a customer’s private cloud or on-premises environment, while early adopters reported efficiency gains including a reported 90% reduction in case-handling time at one financial-services firm.
The launch targets a central enterprise-agent problem: supplying AI agents with the operational context needed to automate workflows that are often undocumented and fragmented across emails, spreadsheets, and employee knowledge.
Artificial intelligence agents have become two a penny in the enterprise today, but just because they’re rapidly being commoditized does not mean organizations know how best to use them.
That’s the challenge a startup called Marble Cognition is trying to solve after raising $3.75 million in pre-seed funding to coincide with its launch today. The round was led by Heartcore and Seedcamp, and saw participation from angel investors that include executives from McKinsey & Co., Mistral AI and a board member of Datadog Inc.
Munich-based Marble was co-founded by the German AI engineers Felix Rösner (pictured, left) and Christophe Schmit (right), who were among the first to realize that AI agents have already become a commodity, used by almost every enterprise in some capacity or other. Most organizations are using AI agents primarily for writing software, but Rösner believes that to see the real value of those autonomous workers, companies need to provide them with the granular operational context that tells them what they actually need to build and automate.
But building this picture is a notoriously difficult challenge because few corporate workflows run according to neat blueprints. Though a study by McKinsey & Co. suggests that it’s theoretically possible to automate 57% of all work hours in the U.S., most companies haven’t gotten anywhere near that goal.
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