Rainmaker raises $100M Series B to scale cloud-seeding drones and win water contracts with hyperscalers and ski resorts
Key Points
- Rainmaker closes $100M Series B to scale autonomous cloud-seeding drones, positioning water scarcity as a strategic resource crisis comparable to China's hundred-million-dollar annual weather modification spend.
- The company has signed one hyperscaler water-offset contract and is in feasibility talks with several others, leveraging real-time measurement capabilities to overcome century-old skepticism around weather modification.
- Rainmaker hedges seasonal and cyclical revenue by operating across multiple Western geographies simultaneously, where even above-average snowfall fails to restore depleted reservoirs like Lake Powell and Lake Mead.
Summary
Read full transcript →Rainmaker closes $100M Series B
Augustus Doricko, CEO of Rainmaker, has closed a $100 million Series B to scale the company's autonomous cloud-seeding drone operations. The round's size still trails what China is spending — Doricko says the Chinese Meteorological Administration spends hundreds of millions of dollars a year on weather modification, treating water as a strategic national resource on par with oil and critical minerals.
That framing is central to Rainmaker's pitch. The Colorado River, the Great Salt Lake, and other Western water systems are depleted to the point where Doricko argues cloud seeding is no longer a novelty — it's the primary viable option for producing new supply.
“The $100,000,000 that we raised, I'm super grateful... The Chinese Meteorological Administration is spending hundreds of millions of dollars a year on their weather modification program because they understand that water and the weather is a strategic capability... Rainmaker already has one deal closed with a hyperscaler, and we're in negotiation and engineering feasibility with multiple others.”
Hyperscalers and ski resorts
Rainmaker has already closed one deal with a hyperscaler to offset that customer's water consumption, and is in engineering feasibility discussions with several others. The commercial logic is straightforward: data centers draw from the same stressed Western reservoirs as agriculture and municipal users, and Rainmaker positions cloud-seeded precipitation as a way to replenish what those facilities consume.
The ski resort pipeline is further along culturally than it might appear. Doricko acknowledges that weather modification has been "full of Fugazi and snake oil for the last hundred years," which kept resort operators skeptical. What shifted their interest was Rainmaker's ability to physically measure and prove results in real time — something earlier players couldn't do. Recent operations in Alaska, Oregon, Idaho, and Utah producing hundreds of millions of gallons of new water gave resorts enough evidence to engage. Doricko flags Swiss cantons as a near-term target for the coming winter season.
Drones over howitzers
The company is staying with autonomous drones rather than ground-based dispersal systems. Doricko says Rainmaker's aircraft can fly in severe atmospheric conditions across a wider flight envelope than most manned aircraft, and that increasing autonomy drives down cost per volume of water delivered. The strategic bet is that more flights and more cost-effective observations compound over time in a way that fixed ground systems can't match. He leaves open the possibility of fixed-wing aircraft in research contexts, but the core deployment model remains drone-based.
Seasonality and geographic hedging
Rainmaker operates a seasonal, cyclically variable business — heavy in winter for snowpack, with annual swings driven by El Niño and La Niña cycles. Doricko says the company hedges this by operating across multiple geographies simultaneously. Even in regions receiving above-average natural snowfall, reservoirs like Lake Powell, Lake Mead, and the Great Salt Lake are so depleted that excess melt above the baseline year is still needed to restore them.
AI as an atmospheric science lever
On AI, Doricko says Rainmaker is seeing genuine acceleration in hypothesis generation and experimentation, specifically citing Google's Astra as a meaningful tool. The model's role isn't just productivity — it's contributing to Rainmaker's atmospheric understanding by critiquing experimental output and informing better models. For a domain that Doricko says has been "historically underinvested in by basically everyone besides commodities desks," that capability compounds quickly when the baseline sensor coverage and modeling sophistication are still being built out.
Every deal, every interview. 5 minutes.
TBPN Digest delivers summaries of the latest fundraises, interviews and tech news from TBPN, every weekday.