Announcement • May 29
Chc Navigation Unveils Next Generation Coprocess for Point Cloud Processing and Survey Deliverables CHC Navigation has announced the launch of the next generation of CoProcess. This latest release marks a significant evolution of CHC Navigation’s professional software, specifically re-engineered to transform extensive LiDAR datasets into structured, engineering-ready deliverables. Building on the foundation of its predecessor, the new CoProcess provides a unified environment that integrates AI-driven classification, terrain modeling, and scan-to-CAD drafting. The software is designed to further streamline the transition from raw field data to final survey outputs, reducing the complexity of professional mapping workflows. To meet the increasing demands of modern geospatial projects, the next-generation CoProcess has been optimized to manage point cloud datasets exceeding 300 GB within a single, continuous workflow. The platform supports the stable rendering of billions of points, allowing users to maintain full data resolution without the need for thinning or segmentation. Efficiency is a core focus of this update. The software’s optimized algorithms can complete terrain classification for a 100 GB dataset in approximately two hours, significantly accelerating project delivery times. CoProcess consolidates the production of survey deliverables by offering an end-to-end toolset that minimizes the need for multiple software applications. Users can generate 2D and 3D CAD models directly from point clouds using refined drafting tools. The platform’s automated classification features facilitate the preparation of structured data, while its terrain surveying module produces high-quality DEMs, DSMs, and contour lines. The software enables precise volume calculations for earthworks and stockpiles, including multi-temporal analysis to track changes over time. The next generation of CoProcess introduces end-to-end workflows that transition from raw data import to final survey outputs within a single environment, reducing dependency on multiple software tools. The platform incorporates standardized processing templates and automation to minimize manual intervention, ensuring greater consistency and reliability across projects. This streamlined approach is supported by intelligent features such as on-the-fly slicing for real-time section views and a fully DWG-native environment, allowing professionals to focus on extraction and design tasks with enhanced productivity. CoProcess is a professional point cloud processing software designed to convert large-scale LiDAR datasets into engineering-ready deliverables. It integrates scan-to-CAD drafting, classification, terrain modeling, and volume calculation within a streamline AI-based workflows. Supporting datasets of over 300 GB, CoProcess enables efficient data processing, reduces manual operations, and accelerates the delivery of accurate survey outputs. Major Estimate Revision • May 22
Consensus EPS estimates fall by 15% The consensus outlook for fiscal year 2026 has been updated. 2026 EPS estimate fell from CN¥1.17 to CN¥1.00 per share. Revenue forecast steady at CN¥4.58b. Net income forecast to grow 31% next year vs 112% growth forecast for Communications industry in China. Consensus price target broadly unchanged at CN¥39.99. Share price fell 4.3% to CN¥29.55 over the past week. Reported Earnings • Apr 17
Full year 2025 earnings: EPS and revenues miss analyst expectations Full year 2025 results: EPS: CN¥0.88 (up from CN¥0.76 in FY 2024). Revenue: CN¥3.70b (up 14% from FY 2024). Net income: CN¥685.4m (up 18% from FY 2024). Profit margin: 19% (in line with FY 2024). Revenue missed analyst estimates by 2.1%. Earnings per share (EPS) also missed analyst estimates by 6.8%. Revenue is forecast to grow 20% p.a. on average during the next 2 years, compared to a 30% growth forecast for the Communications industry in China. Over the last 3 years on average, earnings per share has increased by 22% per year and the company’s share price has also increased by 22% per year. 
