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The Week’s 10 Biggest Funding Rounds: AI, Defense And Space Tech Lead For Large Rounds

This week brought another plethora of large funding rounds for startups and growth-stage companies. Shield AI, a defense tech player focused on autonomy and virtual simulations, secured the largest financing, bringing in $2 billion. Next on the list was drone delivery provider Zipline International, which pulled in a fresh $1.5 billion.

The Week’s 10 Biggest Funding Rounds: AI, Defense And Space Tech Lead For Large Rounds

This week witnessed an abundance of significant funding rounds for startups and growth-stage companies in the United States. Shield AI, a defense technology firm specializing in autonomy and virtual simulations, led with the largest financing, securing $2 billion in equity and $500 million in debt. Zipline International, a drone delivery service, raised $1.5 billion at a $21.5 billion post-money valuation, aiming to expand its manufacturing and hire more staff for a nationwide drone delivery network.

CesiumAstro, a space technology company, closed a $730 million Series D round led by Janus Henderson. Northwood Space, focusing on space infrastructure, received $375 million in Series C funding. Applied Compute, an AI model training platform, raised $350 million at a $3.25 billion valuation, with Elad Gil leading the investment.

Harbinger, specializing in electric trucks, secured $240 million in Series D funding. Sentra, an AI data security provider, closed a $150 million strategic investment. Traversal, building AI agents for enterprise site reliability engineering, raised $120 million at a $1 billion valuation. Ocient, an agentic AI provider for data analytics, received $100 million in Series C funding, and Tutor Intelligence, focused on robot foundation model training, raised $75 million in Series B funding.

Kalepa, an AI tools provider for the insurance industry, also secured $75 million in Series B funding.

Written by urgent.news from Crunchbase News's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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