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Snowflake (Arctic) published LGND AI is the 2026 Snowflake Startup Challenge winner. This talking signal gives public context for research themes, product direction, policy, or launch framing. High-signal details: Startup challenge win, moderate industry interest. · LGND AI is the 2026 Snowflake Startup Challenge winner Skip to content Blog / At Snowflake / Congratulations to the 2026 Startup Challenge Winner: LGND AI JUN 04, 2026 /.... onlylabs links this event to 1 captured evidence page and 6 related writing signals.

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LGND AI is the 2026 Snowflake Startup Challenge winner

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LGND AI is the 2026 Snowflake Startup Challenge winner

Blog / At Snowflake / Congratulations to the 2026 Startup Challenge Winner: LGND AI

JUN 04, 2026 / 3 min read At Snowflake Congratulations to the 2026 Startup Challenge Winner: LGND AI

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The Snowflake Startup Challenge judges started off this year’s finale by describing what they were looking for in a winner: innovative ideas, technology and products that deliver real business value, and team chemistry, grit and passion to tackle big problems. LGND AI delivered on all fronts, becoming the new 2026 Startup Challenge Champion!

Watch the 2026 Startup Challenge Finale On Demand

LGND’s goal is to make the entire planet queryable through imagery. Earth observation data has immense potential value — but it’s also expensive and difficult to use, and almost entirely absent from the AI revolution because LLMs are trained on language.

LGND builds Large Earth Models, or LEMs, that are trained on 800 petabytes of pictures of the planet. With LGND, when you ask an agent “where has there been deforestation in the Amazon this year,” you get an answer that’s grounded in imagery rather than relying solely on written reports.

By leveraging the power of the Snowflake platform, LGND is able to work across multiple types of imagery and modalities, giving them more flexibility at the operational level and at scale.

“We didn't just build the model,” said Jeff Albrecht, Head of Engineering at LGND AI. “We built the entire stack. Models, infrastructure, the agents, all powered by a deep integration into Snowflake across services like Snowpipe, Dynamic Tables, and Cortex Search, to name a few. And we built the application on top.”

Making Earth imagery a factor in business decisions across industries

The team presented three use cases for LGND: insurance and climate risk, government and intelligence work, and AI agents. All of them highlight the immense value of geospatial imagery in business, whether it’s researching how to make properties in wildfire zones more fire resistant or filtering out hotels with active construction sites nearby when planning a vacation. More importantly, making this data consumable and understandable by AI opens a world of opportunities.

“We believe that in the not-too-distant future, our largest user bases won't be just humans — it will be agents, robots and other AI models,” said Nathaniel Manning, CEO of LGND AI. “Every AI that wants to understand the physical world is going to need what we're building.”

The team’s mission, innovation and focus on execution impressed the judges.

“It’s such a broad theme, understanding the Earth as a whole,” said Benoit Dageville, Co-Founder and President of Product at Snowflake. “I like the ambition and the innovation.”

For Denise Persson, CMO of Snowflake, it came back to the mission of the company — “the really important problems they can solve for Earth and humanity, that’s the reason. I love that for all of us.”

A round of applause for the runners-up

Airrived and Twine Security may not be taking home the title, but each will be considered for up to $250,000 in potential funding from Snowflake.

Airrived’s Agentic OS is a foundational operating layer that aims to move enterprises beyond simple AI chatbots toward building, deploying and scaling autonomous AI agents. Companies can fine-tune their models, deploy deep-reasoning agents for complex problems such as investigating a security threat, and orchestrate at scale so multiple agents can work together across different tools and departments. The AetherClaw governance and safety layer supports human-in-the-loop oversight to help ensure autonomous agents follow company rules and security protocols.

Twine Security’s AI digital employees , built using Cortex AI, are specialized autonomous AI agents that can plan, investigate and execute security actions instead of notifying a human to handle them. Twine’s first digital employee, Alex, is an identity and access management expert designed to manage user entitlements, handle user access reviews and proactively address identity-related risks so IT and security teams can focus instead on high-level strategy tasks that need human intelligence.

If you’re a startup building on Snowflake, be sure to check out the Snowflake for Startups program that provides resources to help you build and grow with AI on governed data. And if you want to take home the winner’s snowboard trophy next year, don’t wait: Complete this form to get notified when the 2026 Snowflake Startup Challenge registration opens.

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Startup challenge win, moderate industry interest.