Vancouver, BC, Oct 24, 2026 - (ACN Newswire) - ZenaTech, Inc. (Nasdaq: ZENA)(FSE: 49Q)(BMV: ZENA)("ZenaTech" or the "Company"), a technology solution provider specializing in AI (Artificial Intelligence) drone, Drone as a Service (DaaS), enterprise SaaS, and Quantum Computing solutions, today unveiled its proprietary artificial intelligence software suite and planned integration across its DaaS land survey operations. By pairing ZenaDrone high-density LiDAR (Light Detection and Ranging) data acquisition with automated feature extraction and point cloud classification, ZenaTech plans to accelerate survey-grade data delivery time from days to as little as minutes across commercial land surveying, municipal and infrastructure projects for DaaS clients across North America and around the world. The combined platform is currently in the development and testing stage.ZenaTech, Inc. is a B2i Digital Featured Company. See the company’s in-depth profile at: https://b2idigital.com/zenatech-1
“Land survey delivery has traditionally been limited by manual post-processing, which caps how many projects a survey team can complete,” said Shaun Passley, Ph.D., CEO of ZenaTech. “By integrating our AI software directly into ZenaDrone DaaS operations, we aimto automate the heavily manual work of point cloud classification and CAD linework generation, so the same crews and drones can deliver turn-key, actionable intelligence to clients faster and with consistent quality. As we apply our AI suite across our AI tools growing network of DaaS subsidiaries, we believe it can improve operating efficiency and support the scalable, recurring revenue model at the center of our DaaS strategy.”
The combined platform is designed to bridge hardware data collection with AI-driven point cloud processing. A ZenaDrone land survey drone equipped with high-density LiDAR captures a site as a point cloud, a dataset that can contain billions of individual 3D measurement points. ZenaAI is then intended to run automated geospatial workflows on that data, classifying each point by what it represents, converting the classified data into terrain models and vector drawings, removing noise, tagging infrastructure assets and exporting the results in formats that survey and engineering teams can use directly. Its key planned capabilities include:
Automated Point Cloud Classification: Designed to use deep learning neural networks to rapidly parse billions of 3D LiDAR points, separating ground returns from dense canopy, buildings, utility lines and surface vegetation to generate true Digital Terrain Models (DTM)
Automated Feature Extraction and Linework: Computer vision algorithms are intended to detect and vectorize critical planimetric features, including curb lines, pavement edges, retaining walls and structures, and export them directly into CAD and BIM (Building Information Modeling) formats
Rapid DaaS Turnaround: By replacing manual point-picking and heuristic scripting, the AI software suite is being designed to reduce post-processing workflows by as much as 80% and shorten survey turnaround time, allowing DaaS survey teams to deliver fully classified datasets within hours of flight completion
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