Making AI-ready data accessible
Agimus is a data platform that connects scattered company data, structures it with real meaning and relationships, and gives teams and AI one access point to build on. The gap between what AI can do and what companies can actually deploy almost always comes down to the data underneath.
With origins in applied mathematics and AI research at UCLA and EPFL, Agimus was founded to close that gap. The founding team has built and deployed data-intensive systems in production, and understood what the infrastructure needed to look like for it to actually work.
Based in Palo Alto, with operations across the US and Europe.
Built by the people who understand the problem
Dorian Glon
Founder & CEOUCLA mathematics and economics. Started his first company as an undergraduate. Went on to build AI systems in large-scale enterprise environments: industrial operations, regulated data, complex legacy infrastructure.
Saw firsthand that the bottleneck for AI in production was never the models. It was the data underneath: fragmented, unstructured, inaccessible.
Marco Scialanga
Co-Founder & CTOUCLA applied mathematics. Published at the IEEE International Conference on Big Data as an undergraduate. Master's at EPFL in applied mathematics and machine learning. First-author publication at ACL 2025 on knowledge editing in large language models.
Contributed to Apertus, Switzerland's national open-source LLM suite, as part of EPFL's post-training team. Working at AXA, he saw the disconnect between what AI models could do and the state of the data companies actually had to work with.
Xavier Casanova
Board Director & AdvisorStanford MS in Electrical Engineering. École Polytechnique BS in Mathematics and Computer Science. 20+ years building SaaS companies in Silicon Valley. Multiple companies founded, multiple exits, $10M+ ARR bootstrapped, CEO of a NASDAQ-listed company. Multiple US patents.
Currently building Olakai through Andrew Ng's AI Fund. After two decades of building and scaling software companies, he joined Agimus to help build the data foundation he sees as missing across the industry.
