Grubel Raises €3 Mn to Build AI Systems for Complex Legal Work
Sep 10, 2026 | By Oliver Bennett

Grubel, an AI research lab based in Munich and Tübingen has raised €3 million in pre-Seed funding. The company develops AI systems that can adapt to individual legal cases.
SUMMARY
- Grubel has raised €3 million in pre-Seed funding led by Point Nine.
- The funding will support research, product development, and team expansion.
- Grubel was founded in 2026 by machine-learning researchers Moritz Hardt and Reinhard Heckel.
The new funding will be used to support AI research, product development, and team expansion.
The round was led by Point Nine. Several well-known angel investors also participated, including Jeff Dean, former chief scientist at Google; Chris Ré, Stanford professor and Together AI co-founder; Ion Stoica, UC Berkeley professor and Databricks co-founder; and Gabe Pereyra and Winston Weinberg, co-founders of Harvey.
“Complex legal matters do not come with ready-made training data, task environments, or clear tests of success. We are automating the AI specialisation loop that identifies the right information, curates it into training data and environments, adapts the system to the matter and tests whether its work meets the required standard,” said Reinhard Heckel, co-founder of Grubel.
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“Over the past two to three years, we’ve seen many legal AI companies emerge, but few are pushing the boundaries of AI research in the legal field as ambitiously as Reinhard, Moritz and the Grubel team. We believe their approach can unlock new capabilities in legal AI and over time, other forms of complex knowledge work. We’re excited to support them on this journey,” said Louis Coppey, Partner at Point Nine.
Grubel was founded in 2026 by machine-learning researchers Moritz Hardt and Heckel. The company is building technology that helps AI systems become more specialized for specific types of work.
Grubel’s technology collects and prepares relevant information, adapts AI systems to the legal work they need to handle and checks whether their results meet the required standards.
Hardt is a director at the Max Planck Institute for Intelligent Systems and previously worked as a professor at UC Berkeley and as a researcher at Google Brain. He helped develop test-time training and co-authored Lawma.
Heckel is a TUM professor of machine learning and previously worked at IBM Research. His research focuses on data-focused machine learning and he helped create DataComp-LM and OpenThoughts. Grubel believes that complex work, especially in legal services still depends heavily on skilled human workers while AI has a limited role.
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