Atmo AI

Atmo AI

Atmo AI builds deep learning weather forecasting systems for governments, militaries, and large enterprises that need sharper predictions than legacy numerical models deliver. The company ingests real-time data from satellites, ground stations, radars, and ocean buoys, then runs neural network models that cover nowcasts out to 14-day medium-range outlooks. It sits in the data science stack for organizations where a missed storm or wind shift has operational consequences, not just a ruined picnic.

Where traditional numerical weather prediction leans on supercomputers and fixed grid resolutions, Atmo claims forecasts up to 40,000 times faster and up to 50% more accurate on major variables, with grids as fine as 1 km by 1 km for microclimate detail. That resolution gap matters for launch sites, island nations, and defense bases where a county-level forecast hides the local wind shear. The trade-off is access: Atmo sells custom deployments, not a consumer app you open for tomorrow's rain.

National weather agencies, defense commands, and enterprise risk teams use Atmo when they need site-specific forecasts backed by live production contracts. Deployments cited on Atmo's site include the U.S. Air Force, U.S. Navy, the Philippines national government, Cape Canaveral launch operations, and Tuvalu's national forecasting rollout.

Top Features:
  1. Pulls real-time weather data from satellites, ground stations, radars, and ocean buoys worldwide

  2. Delivers forecasts up to 40,000 times faster than traditional numerical weather models

  3. Reports up to 50% higher accuracy on major variables from 24-hour nowcasts to 14-day outlooks

  4. Resolves microclimates with grid detail down to 1 km by 1 km

  5. Runs live production deployments for the U.S. Air Force, Navy, and Philippines national government

Pros:
  1. Claims up to 50% accuracy gains and 40,000x faster inference than traditional numerical models.

  2. 1 km grid resolution targets microclimates that coarse national forecasts miss.

  3. Live deployments with U.S. military branches and national governments validate production readiness.

Cons:
  1. No public pricing or self-serve signup; every deployment requires a sales conversation.

  2. Interactive demos exist but full forecasting access is limited to contracted customers.

  3. Enterprise focus means small teams cannot evaluate the product without a formal engagement.

FAQs:

What does Atmo AI forecast?

Atmo AI produces weather forecasts from 24-hour nowcasts through 14-day medium-range outlooks. Its deep learning models ingest satellite, radar, ground station, and buoy data to predict major prognostic and diagnostic variables at resolutions down to 1 km grids.

Who uses Atmo AI?

Atmo AI serves governments, militaries, and enterprises that need high-resolution forecasts for critical operations. Named customers on its site include the U.S. Air Force, U.S. Navy, the Philippines national government, and Cape Canaveral launch weather teams.

How accurate is Atmo AI?

Atmo AI states its models are up to 50% more accurate than today's most advanced forecasts across major variables. The company also highlights up to 100 times greater spatial detail than conventional grids, with 1 km resolution for microclimate forecasting.

Is Atmo AI free to use?

No. Atmo AI sells custom forecasting deployments to governments, militaries, and enterprises. There is no public self-serve pricing page; teams book a meeting through the contact form on atmo.ai to discuss a deployment.

Where is Atmo AI headquartered?

Atmo AI is headquartered in San Francisco, California at 1266 Harrison St. The company was founded in 2020 and lists general inquiries at [email protected] and media requests at [email protected] on its website.

Does Atmo AI offer a public forecast app?

Atmo AI operates interactive forecast demos on subdomains like earth.atmo.ai and sf.atmo.ai, but its core product is enterprise and government forecasting infrastructure. Production systems are tailored to each customer's geography and operational requirements.

Category:

Pricing:

Paid

Tags:

Weather Forecasting
Deep Learning
Meteorology
Microclimate Modeling
Government Weather Systems
Defense Forecasting
AI Meteorology
Forecasting Technology

Tech used:

jQuery
Webflow
Cloudflare
Amazon CloudFront
Google Cloud
Google Fonts
Font Awesome
GSAP
Laravel
Ruby
Styled Components
Tailwind CSS

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