LGND Raises $9M to Build the “ChatGPT for the Earth”
LGND leverages AI models and advanced compression techniques to make Earth observation data exponentially more accessible and cost-effective.
LGND is making geospatial data as searchable and useful as language. Co-founded by CEO Nathaniel Manning, CPO Dan Hammer, and Chief Scientist Bruno Sánchez-Andrade Nuño, the company just closed a $9 million seed round led by Javelin Venture Partners, with backing from Everywhere Ventures, AENU, Clocktower Ventures, MCJ Collective, Ridgeline, Space Capital, and others.
Their aim: to transform the 100+ terabytes of daily Earth observation data into actionable insights for enterprises, governments, and eventually consumers.
From Fire Breaks to Flexible Search
At the heart of LGND’s platform are geographic vector embeddings—compressed, intelligent summaries of spatial data that allow AI to recognize patterns across the Earth’s surface. Instead of building new models for each geospatial task (like mapping fire breaks in California), users can pose natural language questions and get rapid, meaningful results.
“We’re looking to make people dramatically more efficient, not replace them,” said Nuño in the TechCrunch interview. LGND has built an enterprise app and an API that help users detect infrastructure, assess disaster risk, monitor vegetation loss, and more—without the steep learning curve of traditional GIS tools. The embeddings act like a precomputed layer of intelligence, drastically reducing the time and compute needed to extract insights.
Laying the Groundwork for GeoAI at Scale
Beyond enterprise use cases, Manning envisions a world where consumers benefit, too. Imagine a travel planner that doesn’t just find homes near the beach—it understands whether it’s white sand, low on seaweed in February, and free from nearby construction.
“Embeddings do the heavy lifting upfront,” Nuño said. “They summarize 90% of the compute you’d otherwise have to run every time.”
Manning sees it as a foundational opportunity. Rather than building tools one use case at a time, LGND is creating infrastructure that could power the next generation of GeoAI products.
“We want to be the Standard Oil for this data,” he told TechCrunch.
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