LGND AI has raised $9 million to expand its geospatial AI platform, aiming to make complex Earth data more accessible and actionable for industries like climate, insurance, logistics, and AI.
LGND AI, a company on a mission to make Earth data more intuitive and usable for both humans and AI, has raised $9 million in a funding round led by Javelin Venture Partners.
The investment will accelerate LGND’s development of geospatial AI tools that transform complex Earth data into actionable insights across industries—from climate resilience and insurance to logistics and AI development.
The round includes backing from firms such as AENU and MCJ Collective, along with notable angel investors like Suzanne DiBianca (Chief Impact Officer at Salesforce) and John Hanke (creator of Keyhole and Google Maps).
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Founded by experts in Earth observation, AI, and public impact, LGND is reimagining how spatial data is processed and applied. The company operates remotely with hubs in the Bay Area, New York, and Copenhagen.
LGND’s vision: Make Earth data intuitive, accessible, and actionable—so that more people and systems can respond to the challenges of our changing world.
Earth observation data plays a critical role in global challenges like climate adaptation, disaster response, and infrastructure planning. Yet most of this data remains underutilized due to high costs and technical complexity.
LGND is tackling this gap by using geographic embeddings—advanced machine learning representations of spatial data—to create a platform that simplifies how users develop, refine, and deploy geospatial insights.
“Our mission is to make Earth data universally accessible and actionable through AI,” said Nathaniel Manning, CEO and cofounder of LGND. “We’re making Earth understandable to people—and to AI.”
Traditional maps offer snapshots; LGND is building dynamic, real-time systems. At the core of its platform is a “geo-embeddings factory” that produces scalable, context-rich Earth datasets at a fraction of the cost of legacy computer vision methods.
Key capabilities include:
The platform learns and improves with use, helping analysts, developers, and AI models make smarter decisions faster.
“Geographic embeddings are emerging as a foundational data object for geospatial systems,” said Dan Hammer, cofounder and Chief Product Officer. “LGND is building the infrastructure to serve these at scale.”
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With the new funding, LGND plans to:
“This is not an incremental change—it’s a rebuild of how we interact with the planet’s data,” said Bruno Sánchez–Andrade Nuño, LGND’s Chief Science Officer.
LGND’s tools are designed for teams that need to move quickly—whether analyzing environmental risk, assessing climate threats, or responding to supply chain disruptions.
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