Picterra vs. traditional machine learning for geospatial data

About this webinar

There are many steps and people required to bring a geospatial ML project from concept to deployment. No wonder it typically takes months – if not years – to use ML models in practice and return a positive ROI, if they even make it into production at all.

By automating several steps of the ML lifecycle, Picterra shortens the time to insight by up to 95% compared to a project using traditional machine learning for geospatial data. It means your GIS and data science teams can spend more time on what actually matters: turning geospatial analysis into actionable insights.

Register today to hear software and ML engineers Julien and Stéphane discuss the Picterra platform’s ML capabilities and what sets it apart from traditional geospatial platforms.