The Most Advanced AI Weather Model in the World Relies on Render and Better Stack

A conversation with Kai Marshland, founder of WindBorne Systems

Weather forecasting is one of the most computationally and data-intensive challenges in the world—literally so complex that early computer weather models in the 1960s led Edward Lorenz to develop chaos theory. WindBorne Systems is advancing the field by combining proprietary long-duration smart weather balloons with the world’s most accurate AI-based weather model.

Our balloons can fly for over 50 days at a time, circumnavigating the globe and collecting the data everyone else is missing,” says Kai Marshland, WindBorne’s founder. “Because 85% of the Earth’s atmosphere is effectively invisible to humanity, filling in this data gap allows us to deliver much better initial conditions to our weather models. Think of it like the prompt to an LLM—you get a much more accurate result.

To support this cutting-edge operation, WindBorne requires a highly reliable infrastructure to manage its global fleet of balloons, process massive amounts of atmospheric data, and deliver high-availability forecasts to customers like NOAA, the U.S. Air Force, and many more.

For example, we work with the Gates Foundation to provide weather data to farmers in Sub-Saharan Africa. That API runs on Render, alongside our mission control system and customer-facing forecast viewers.

Real-time Observability Using Render and Better Stack

For WindBorne, monitoring a global fleet of autonomous weather balloons requires the ability to track system performance, debug real-time telemetry, and ensure mission-critical uptime.

We can’t afford downtime when our customers depend on real-time forecasts, and we can’t risk losing connection with our balloons mid-flight,” Kai explains. “We need high availability, high reliability, and fast development velocity.

To achieve this, they rely on Render for infrastructure and Better Stack for observability. With Render’s launch of OpenTelemetry metrics streaming, they’re now integrating infrastructure metrics (CPU, RAM, etc.) alongside logs in Better Stack, giving them a unified view of their entire system.

A real example: We had a discrepancy in how our balloons were venting gas to control their altitude,” Kai explains. “We had switched from a larger balloon envelope to a smaller one, and our control algorithm wasn’t adjusting correctly. We explored logs in Better Stack to track down when and where messages were being sent to the balloon over satellite communications. We found that the envelope setting wasn’t being applied at the expected time, which let us fix the issue.

What’s Next for WindBorne?

With WindBorne’s rapid growth, the company is already pushing the limits of today’s weather forecasting technology.

We’ve gone from having one balloon aloft at a time to 100 in just the last two years, and we need to scale to 10,000,” Kai explains. “That’s an entirely new scale of infrastructure challenge.

As they expand their global sensor network and scale their mission control systems, WindBorne is also building new forecasting tools for energy traders—helping them anticipate weather-driven shifts in power markets at a glance.

With even more real-time data flowing through their platform, Render and Better Stack will remain critical to ensuring high availability, fast debugging, and seamless scaling—keeping WindBorne at the forefront of AI-powered weather intelligence.

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