Asset Inventory &
Utility Mapping
Reflektar deploys survey-grade LiDAR with millimeter precision and AI technology to automatically inventory, classify, and map infrastructure assets and utilities at scale. From signs and guardrails to utility poles and powerlines, every asset is detected, attributed, and delivered in your preferred format.

What's Included
Rapid Processing
Our in-house algorithms can process extensive stretches of highway data in just hours, delivering detailed asset and utility information in a highly efficient manner.
Comprehensive Data Collection
Capture and categorize all major assets — from signs and guardrails to utility poles and powerlines — in a single organized, detailed digital inventory.
AI-Driven Asset Classification
Machine learning models automatically detect and classify each asset type, assign condition ratings, and extract key attributes without manual intervention.
Cloud-Based GIS Inventory
All assets are stored in a centralized, cloud-based GIS environment accessible through the Reflektar Platform for ongoing management and reporting.
Why Choose Reflektar
Faster Data Collection
Reduce data collection and processing times from months to days with remote sensing and AI automation.
Enhanced Infrastructure Management
A centralized cloud-based GIS inventory makes it easier to track asset conditions, plan repairs, and manage infrastructure over time.
Reduced Manual Labor
Automated AI-driven processing eliminates extensive manual fieldwork, cutting labor costs and minimizing human error.
Improved Data Accuracy
Survey-grade precision ensures every asset is accurately mapped, supporting effective maintenance planning.
Scalable Across Networks
Process single roads or entire highway networks with the same efficient workflow and consistent output quality.
Standard Format Exports
Deliver asset data in GIS, CAD, or spreadsheet formats compatible with existing asset management systems.
Ready to Get Started?
Schedule a demo or contact our team to see how Reflektar can transform your projects.