ZenaTech, a business technology solution provider specializing in AI (Artificial Intelligence) drones, Drone as a Service (DaaS), Enterprise SaaS, and Quantum Computing solutions, announces the successful development of its first quantum computing prototype consisting of a framework for the rapid analysis and processing of large datasets for its AI drone solutions. Using weather forecasting algorithms as part of its Clear Sky project as a test case, the company has created a precedent framework for real time analysis of massive amounts of data that can be captured through AI drone sensors while in the air.
The Company envisions commercial applications ranging from highly efficient precision agriculture to predictive energy infrastructure inspections. Defense applications include enhancing real-time battlefield decision-making with faster and more precise threat detection, reconnaissance, and advance electronic warfare capabilities.
“We’re not just building smarter drones, we’re building a quantum-intelligent edge where data becomes decisions in an instant, whether it’s a battlefield or a farm field,” said Shaun Passley, Ph.D., ZenaTech CEO. “We believe this quantum framework we are creating is just the beginning as we’ve now demonstrated it can use it for large datasets. We plan to keep expanding R&D capabilities, with the goal of growing our team of 6 to 25 over the coming months. The end goal is clear: accelerate time to market, reduce operational costs, and lead the industry as a true innovator,” added Dr. Passley.
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ZenaTech’s Clear Sky project is one of the company’s quantum computing R&D initiatives focused on weather forecasting that will use AI drones and drone fleets plus quantum to better predict localized weather for more accurate prediction of extreme weather events saving lives and reducing costs and destruction. The weather application and algorithms used for the prototype track and analyze multiple key atmospheric parameters such as temperature, humidity, wind, barometric pressure, and precipitation. Internal testing using historical open-source data has shown a high degree of accuracy with trusted weather platforms and actual data, validating both its accuracy and reliability.
Quantum computing combined with AI-powered drone applications enables disruptive speed, precision, and autonomy by dramatically accelerating data analysis, optimizing complex decisions, and enhancing real-time responsiveness. In commercial sectors, this means drones can autonomously inspect vast energy grids or farmland, instantly analyze multispectral data, and adjust actions on the fly—leading to lower costs and higher productivity in agriculture, logistics, and infrastructure. In defense, the same capabilities empower autonomous surveillance drones to process sensor data and identify threats in real time, coordinate swarm or drone fleet movements, and dynamically adapt to changing battlefield conditions—all with minimal human input. This fusion of technologies allows drones to make faster, smarter decisions in unpredictable, data-intensive environments—reshaping what’s possible across industries.
For weather forecasting, quantum computing can rapidly process and simulate complex atmospheric models by analyzing massive datasets from AI-enabled drones equipped with weather sensors, LiDAR, and imaging systems. This allows for highly accurate, real-time weather forecasting and microclimate prediction, improving response times for disaster management, aviation safety, and environmental monitoring.
Source: Globenewswire
