AI Startup MarvelX Raises $6 Million to Revolutionize Insurance Back-Office Operations
AI Startup MarvelX Raises $6 Million to Revolutionize Insurance Back-Office Operations
Dutch AI startup MarvelX AI has secured $6 million in seed funding, as it sets out to transform insurance back-office operations through automation and intelligent systems.

The funding round was led by EQT Ventures, with participation from a group of prominent angel investors connected to DeepMind, Plaid, Elastic, Coinbase, Partior, and Microsoft.

Founded earlier this year by data scientist Ali el Hassouni, MarvelX is tackling what it sees as a major pain point in financial services: the inefficiency of manual processes in insurance operations. The company is launching ClaimOS MaX, a proprietary platform designed to automate workflows—starting with claims processing.

ClaimOS MaX integrates with existing IT infrastructure, helping insurers streamline back-office operations, reduce manual workloads, and improve efficiency. Among the early adopters is Companjon, a European provider of embedded insurance solutions.

“MarvelX is building a next-generation vertical AI company in one of the most operationally complex and underserved industries,” said Tom Mendoza, Partner at EQT Ventures. “Their team combines deep AI expertise with a real understanding of the regulatory and data challenges faced by insurers, banks, and wealth managers. We’re proud to partner with them to help transform this space.”

Commenting on the vision behind MarvelX, el Hassouni said: “At MarvelX, we are building the infrastructure required to make AI truly operational. Our platform orchestrates intelligent agents that integrate with existing systems, follow domain-specific logic, and adapt to evolving rules. The result is a transition from repetitive, manual work to reliable, intelligent operations that scale.”

With its fresh capital, MarvelX plans to accelerate development, expand its team, and bring its platform to more insurance and financial services providers globally.

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