30x
Processing efficiencyAutomatically process, classify and QA captured LiDAR at 30x efficiency and up to 99% accuracy.
Automate point cloud classification at scale and save time.
Fragmented workflows often create inaccuracy and slowness in LiDAR classification, vectorization, and analysis, requiring intensive manual quality reviews that drive up operating costs and project delays.
Neara’s Spatial Modules* are purpose-built to simplify and streamline all stages of geospatial data processing. Underpinned by ML & AI, they comprise an integrated end-to-end solution that hosts, manages, processes, classifies, vectorizes, & analyzes LiDAR data on a massive scale.
Process and classify noisy LiDAR
Neara AutoProcessing ingests unclassified and noisy LiDAR and returns a fully classified and denoised dataset.
Auto generate a 3D vector model
Neara automatically generates a 3D vector model from a classified point cloud dataset, and intelligently reclassifies LiDAR based on heuristics and relationship to the model.
LiDAR point cloud viewer & spatial analytics at-scale
Conduct LiDAR spatial analytics at-scale to visualize and explore clearance to ground/conductors, vegetation encroachment, etc.
*Neara digital twin build not required for Spatial Modules.
Processing efficiencyAutomatically process, classify and QA captured LiDAR at 30x efficiency and up to 99% accuracy.
Faster risk identificationTime-to-analysis savings made possible through a robust analytics platform using intelligent and predictive analytics.
Time to productionLiDAR teams can review and productionalize datasets within 24 hours of data ingestion.
Cost savingsUp to 10x cost savings through automation of LiDAR classification, processing and analysis using AI/ML.
Contact us to learn more, schedule a demo, inquire about a pilot project, or discuss other needs.