Earth has always been big data. The question has never been whether the planet’s telling a story. It’s whether anyone’s listening in a language AI can understand. LGND AI, Inc. just dropped the Rosetta Stone for Earth.
$9 million in seed capital. Led by Javelin Venture Partners. With heavyweight backing from AENU, Space Capital, Overture, Ridgeline, MCJ, Coalition Operators, Clocktower Ventures, and angels like John Hanke (yeah, the Google Earth guy), Karim Atiyeh (Ramp CTO), and Salesforce’s own Suzanne DiBianca. If that lineup doesn’t get your eyebrows up, your signal-to-noise ratio might be busted.
Let’s not skim past this. LGND isn’t peddling another “geospatial platform” with a fresh coat of venture gloss. Nathaniel Manning (formerly at USAID, Kettle, Ushahidi), Dan Hammer (PhD, UC Berkeley, founding brain behind Earth Genome, Global Forest Watch, Clay), and Bruno Sánchez-Andrade Nuño (climate science Jedi with a PhD in Astrophysics) didn’t come here to draw maps. They came to rewire how Earth is digitized.
Their product? A “geo-embeddings factory” that turns satellite imagery and spatial data into precomputed vector embeddings, real-time, queryable, and ready for integration into AI agents and compute pipelines. Think LangChain meets Landsat. The result? You can now interrogate the Earth like it’s ChatGPT trained on tectonic plates, deforestation, and your supply chain’s weakest link.
The no-code geospatial app is on deck. Enterprise SDKs are already in the wild. Pilots are underway with insurers, logistics firms, and anyone serious about modeling wildfire risk, sniffing out illegal mining, or making their AI workflows Earth-aware. In just nine months post-founding, they’ve deployed across North America and Europe. They’re cloud-native on AWS and GCP, SOC 2 Type I compliance is in progress, and their embedding tech cuts compute costs by over 90%. That’s not a marginal gain, that’s a tectonic shift.
This isn’t just a company; it’s infrastructure. LGND is aiming for the foundational layer of the next generation of Earth-data intelligence. From risk management and climate adaptation to defense logistics and infrastructure analytics, the planet is their API, and they’re teaching AI how to speak its language fluently.
