Case Study: Preligens scales geospatial intelligence R&D with Valohai

Building a safer world with AI-powered geospatial intelligence

Preligens, a company that builds AI-powered geospatial intelligence software, faced the challenge of managing the complex infrastructure required for its large-scale deep learning model training. With a rapidly growing team of 50 data scientists, they needed a robust MLOps solution to industrialize their workflows, orchestrate jobs, and automatically track thousands of experiments without losing work or requiring a large infrastructure team.

To solve this, Preligens implemented the Valohai MLOps platform. Valohai provided a shared platform with automatic versioning, managed their hybrid cloud infrastructure across multiple providers, and integrated seamlessly with Preligens' proprietary framework via its API. This solution allowed Preligens to keep its infrastructure team small while dramatically scaling its data science operations, ensuring all experimentation was tracked and reproducible, and giving analysts the intelligence needed to build a safer world.

Preligens

Renaud Allioux

CTO & Co-Founder