GeoCue Simplifies 3D Data with New AI and Photogrammetry Tools

DENVER, CO – February 17, 2026 – Amidst the buzz of AI and automation dominating Geo Week 2026, geospatial software provider GeoCue has made a significant move to democratize advanced point cloud processing. The company today unveiled four new software add-ons for its flagship LP360 Drone software, designed to automate complex classification and photogrammetry workflows with unprecedented simplicity. The new offerings—AI Ground+, AI Forestry, AI Utilities, and the 3D Photo Engine—leverage pre-trained AI models and cloud computing to deliver powerful results with just a few clicks.

The announcement comes as the geospatial industry grapples with processing ever-larger datasets from LiDAR and drone imagery. While AI has long been promised as a solution, its implementation often requires specialized machine learning knowledge, significant computing power, and complex training procedures. GeoCue aims to eliminate these barriers, positioning its new tools as accessible solutions for surveying, civil engineering, forestry, and utility professionals regardless of their AI expertise.

Automating Analysis with "Click-Button" AI

At the heart of GeoCue's announcement are three new AI-powered classification tools that build upon the success of its initial AI Ground Classification feature. These add-ons operate on a simple premise: users can upload their point cloud data and receive highly detailed, classified results without needing to configure complex parameters or provide their own training data.

“Our development team is always using feedback from our users to improve and adjust LP360,” said Frank Darmayan, COO of GeoCue Group. “We saw a tremendous response to our automatic AI Ground Classification tool in version 2025, and these three new advanced AI features were developed to continue serving our customer base and make extracting classes easier and more in line with applications and deliverables.”

The new AI tools are tailored for specific industry needs:
* AI Ground+: An expansion of the original ground classification, this cloud-based service segments point clouds into multiple above-ground classes, including vegetation, buildings, vehicles, bridge decks, and water surfaces. Priced at $2,640 per year, it is designed for general mapping projects that require comprehensive feature extraction.
* AI Forestry: This specialized add-on automates tree segmentation and delivers forestry-specific outputs. It identifies individual trees, calculates trunk heights, estimates diameter at breast height (DBH), and generates canopy models. At $5,280 per year, it provides foresters with ready-to-use data for inventory, planning, and management.
* AI Utilities: Developed for transmission line workflows, this tool automatically identifies critical infrastructure components like wires, towers, poles, and insulators from point cloud data. It provides both classified points and vector outputs, streamlining the analysis required for maintenance and vegetation encroachment studies. It is also priced at $5,280 annually.

Each of these AI add-ons requires the base LP360 Drone software and operates on a subscription model that includes a set number of monthly processing jobs, making advanced analysis available as a predictable operational expense.

A New Competitive Landscape for Geospatial AI

GeoCue's focus on pre-trained, user-friendly AI places it in a distinct position within a competitive market. Major industry players like Trimble and Esri have also integrated powerful AI and machine learning capabilities into their software suites. For instance, Trimble Business Center (TBC) and Esri’s ArcGIS Pro both offer sophisticated tools for point cloud classification. However, these platforms often provide, and sometimes require, users to train their own models on custom datasets. While this offers immense flexibility for unique applications, it can also present a steep learning curve and demand significant investment in time and resources.

By offering a "black box" solution where the deep learning models are already trained, GeoCue is betting on the appeal of simplicity and efficiency. This approach resonates with a large segment of the market that prioritizes rapid, reliable results over the ability to fine-tune algorithms. As one industry analyst covering the Geo Week event noted, "The majority of users aren't data scientists; they're surveyors or engineers. They need tools that solve a problem, not create a new research project. The 'push-button' philosophy, if accurate and reliable, could be a game-changer for adoption."

This strategy directly addresses a key theme at Geo Week 2026: using technology to augment human expertise, not replace it. By automating the most tedious and time-consuming aspects of data classification, these tools promise to free up professionals to focus on higher-level analysis, quality control, and decision-making.

Integrating Worlds: The 3D Photo Engine

Beyond pure AI classification, GeoCue also introduced the 3D Photo Engine, an add-on aimed at bridging the gap between LiDAR and photogrammetry. This tool enhances the integration of aerial imagery within the LP360 environment, addressing a common challenge for mappers who use both sensors to create comprehensive 3D deliverables.

“LP360 continues to refine our graphical user interface and workflow to make it easier to extract value from both LiDAR and aerial imagery,” stated Vivien Heriard-Dubreuil, CEO of mdGroup, GeoCue's parent company. “With the 3D Photo Engine and the new Photo Ribbon, users can generate an enhanced orthophoto by leveraging ground LiDAR data as a reference, achieve higher-quality point cloud colorization than standard geocoding, and finish with a quality report that documents processing results, all within a simple, guided workflow inside LP360.”

Priced at $2,475 per year, the 3D Photo Engine enables users to produce superior aerial photo products. By using the highly accurate ground surface from LiDAR data as a control for orthophoto generation, it can improve results beyond what is possible with imagery-only workflows. It also provides a more rigorous method for colorizing LiDAR point clouds, resulting in more visually consistent and realistic 3D models. Furthermore, the engine supports the creation of 3D textured meshes, a popular deliverable for visualization and use in third-party applications.

This focus on a holistic workflow underscores a broader industry trend toward fused data products. Clients increasingly expect comprehensive 3D models that combine the geometric accuracy of LiDAR with the photorealistic texture of high-resolution imagery. The 3D Photo Engine provides a streamlined path to creating these high-value deliverables directly within a single software environment. The new tools will be showcased throughout Geo Week, where attendees can see live demonstrations and discuss how they can be integrated into their existing survey, mapping, and inspection operations.