Powering geospatial data analytics with machine learning: Why we invested in Picterra

We are excited to announce our Series A investment in Lausanne-based Picterra, alongside VI Partners and ACE & Co. Picterra provides a machine learning DevOps platform for geospatial data analytics.

The space industry has changed tremendously since the launch of Sputnik 1. Thanks to high levels of private funding and advances in technology, satellite launch costs have come down by orders of magnitude, and geospatial data is becoming ever more abundant. This is opening up exciting new commercial opportunities and fueling demand across industries for intelligence derived from geospatial data.

Yet, turning geospatial data into actionable insights is complex, time-consuming and expensive — especially for enterprises that do not have the required in-house machine learning capabilities. Picterra provides a solution for just that: a platform that allows enterprises to train machine learning models to analyze geospatial data for their own specific use case — without the need to build up ML expertise in-house.

Here’s why we invested in Picterra.

A large and growing opportunity

Thanks to tremendous technological advances, the cost and complexity of acquiring satellite imagery are declining rapidly. Add to that the abundance of aerial images from aircrafts or drone usage, as well as the emergence of imagery sourcing platforms, and geospatial data is now widely accessible for enterprises. This unlocks new commercial opportunities. Exemplary use cases include precision agriculture, infrastructure maintenance, risk management for insurance or route monitoring for maritime companies.

However, there is a need for intelligence solutions on top of the acquisition of geospatial data to generate actionable insights and create value for enterprises. Analyzing earth observation images at scale requires machine learning models to detect objects, patterns and changes over time. Building and training these models in-house requires time, resources and highly specialized knowledge — opening up a market for external solutions. The opportunity for satellite data processing, analytics, insights and decision support is already a multi-billion market, but is expected to more than double in the next ten years.

We are convinced that Picterra is well positioned to address this opportunity with their solution, as the company is democratizing access to advanced tools previously only accessible to data scientists. This makes their product highly scalable and able to be widely used in business in a way that’s never been seen before.

Clear value proposition proven by strong traction

Picterra provides a clear value proposition to its customers: they can build their own AI models to analyze geospatial data using pre-trained machine learning algorithms. This allows enterprises to develop their analytics tools 100x faster at a fraction of the cost, given that they no longer need to build highly specialized teams in-house. Geospatial data analytics therefore becomes commercially viable to many enterprises that previously did not have the means, opening up new business opportunities.

This is reflected in Picterra’s significant traction with large global enterprise accounts and strong customer references. Clients span across industries from infrastructure, engineering and mining to agriculture, FMCG and automotive, with use cases ranging from construction monitoring and risk management to precision agriculture, forestry management, environmental monitoring and auditing.

An experienced team with passion and purpose

The Picterra team combines strong technical expertise and relevant domain knowledge. Frank, Co-Founder and COO, holds a Ph.D. in machine learning applied to geospatial data from EPFL and spent nine years working in the geospatial analytics space. His co-founder Pierrick, CEO, gained valuable experience in technology consulting and business development in the space industry before co-founding Picterra. Both are relentless in their quest to make Picterra the leader of its category, and are guided by their mission to democratize access to earth observation information and analytics with an emphasis on positive social and environmental impact.

They have assembled a team of industry experts in machine learning, data science and software engineering as well as experienced enterprise sales managers. Combining all these skill sets and experience, we are convinced Picterra has built the right team to execute its vision of becoming the leading machine learning platform for geospatial analytics.

Want to know more about Picterra? Visit their website or get in touch with us.