PalniES delivers high-quality geospatial annotation and labelling services that turn raw imagery and point cloud data into actionable intelligence for infrastructure, network planning, and AI-driven applications. From 2D imagery tagging to 3D point cloud annotation, our experts provide precise, validated datasets that enable machine learning, automated asset detection, and advanced modeling workflows.
Accurate annotation is critical for creating HD maps, supporting infrastructure monitoring, and developing AI systems that require reliable spatial context. By combining human expertise with AI-assisted tools, PalniES ensures consistent quality, comprehensive coverage, and scalable annotation solutions that integrate seamlessly into GIS, CAD, BIM, and AI pipelines.
PalniES delivers end-to-end geospatial annotation and labelling services that convert raw imagery and point cloud datasets into structured, high-fidelity information for AI, machine learning, and advanced analytics. We meticulously tag features across aerial imagery, street-level photography, satellite imagery, and LiDAR point clouds to create training-ready datasets that power automated asset detection, scene analysis, and predictive modeling.
Our annotation specialists leverage industry-standard tools and advanced workflows to classify objects, draw bounding boxes, generate polygon masks, and annotate 3D point clouds with precision. Each dataset is validated for accuracy, consistency, and completeness, ensuring that your AI and machine learning models perform reliably across diverse infrastructure, telecom, utility, and transportation applications.
With PalniES, raw geospatial data becomes a structured, actionable foundation that drives analytics, operational insight, and AI-ready intelligence for your projects.
Accurate annotations for ML/AI model development
2D imagery, 3D point clouds, video, and satellite data
Infrastructure, telecom, utility, and transportation knowledge
By transforming raw geospatial data into curated, machine-learning-ready information, PalniES enables smarter decision-making, enhances operational efficiency, and accelerates the deployment of AI-powered geospatial solutions.
Object detection bounding boxes, semantic segmentation, polygon annotation, and multi-class labeling for aerial, satellite, and street-level imagery.
LIDAR point cloud classification, 3D bounding boxes, instance segmentation, and feature labeling for autonomous vehicle and infrastructure applications.
Infrastructure asset tagging including poles, signs, manholes, hydrants, vegetation, buildings, and road markings from geospatial imagery and scans.
OCR-assisted text extraction, attribute population, metadata tagging, and structured data creation from unstructured imagery sources.
Multi-temporal image comparison, change labeling, damage assessment annotation, and construction progress tracking for monitoring applications.
Multi-tier QC workflows, inter-annotator agreement checks, accuracy validation, and annotation quality metrics ensuring training data reliability.
Taxonomy definition, annotation guidelines, tool configuration
Annotator training, reference examples, test set validation
Multi-annotator workflows, progress tracking, task assignment
Multi-tier review, accuracy checks, consistency validation
Format conversion, train/val/test split, documentation
Taxonomy definition, annotation guidelines, tool configuration
Annotator training, reference examples, test set validation
Multi-annotator workflows, progress tracking, task assignment
Multi-tier review, accuracy checks, consistency validation
Format conversion, train/val/test split, documentation
Street-level imagery annotation with vehicle, pedestrian, road sign, and lane marking labels for self-driving car perception system development.
Utility pole, sign, manhole, hydrant, and roadway asset labeling for automated inventory systems and AI-powered asset management platforms.
Aerial imagery annotation identifying poles, cables, equipment, and clearance zones supporting automated network planning and design tools.
Time-series imagery annotation tracking construction progress, site changes, and development activity for automated monitoring and reporting systems.
High-performing AI and machine learning models start with precise, reliable training data. PalniES transforms raw imagery and LiDAR point clouds into expertly annotated, validated datasets—ready to power asset detection, automated feature extraction, and advanced analytics.
Our approach ensures accuracy, consistency, and full integration with your AI pipelines, giving your teams the confidence to deploy models that deliver real-world results.