Apollo Advisory helps utilities unify drone, LiDAR, and helicopter inspection data into a single platform, automating workflows and turning raw imagery into actionable decisions. The solution integrates directly with Esri and Clearion, enabling teams to manage assets and identify risks without switching between disconnected systems. By replacing manual, spreadsheet-based processes, Apollo Advisory reduces the risk of overlooked infrastructure trends.
Funding
Funding not disclosed
Founders
Product
Problem
Utilities spend millions annually on drone, LiDAR, and helicopter inspections, yet the resulting data remains scattered across disconnected systems, spreadsheets, and static reports. This fragmentation forces manual workflows that slow decision-making and cause critical infrastructure risks and trends to be overlooked.
Solution
Apollo Advisory provides a unified platform that consolidates inspection data from multiple sources into a single, integrated environment. The solution automates data processing and workflow management, transforming raw imagery into clear, actionable insights. It is purpose-built to operate within Esri and Clearion, allowing utilities to leverage their existing GIS and asset management investments. By automating routine analysis and reporting, Apollo Advisory helps teams identify risks earlier and respond faster, reducing reliance on manual data handling.
Target Audience
Primary customers are utility companies and infrastructure operators that conduct aerial inspections and need to streamline data management, analysis, and reporting within their existing Esri or Clearion environments.
Features
- Centralized ingestion of drone, LiDAR, and helicopter inspection data into one platform
- Automated workflow engine that streamlines data processing, review, and approval cycles
- Native integration with Esri and Clearion for direct access to GIS and asset management systems
- Conversion of raw imagery into structured, decision-ready insights and visualizations
- Risk and trend detection capabilities that flag anomalies across inspection datasets