2023

AiDash Intelligent Vegetation Management System (IVMS)

Satellite-first SaaS platform for utility vegetation risk management, automating inspection and compliance for large infrastructure firms. See also: IVMS FieldPro Mobile App.

Satellite
Utilities
AI
SaaS

Case Study Overview

A comprehensive breakdown of the product management approach, from problem discovery to measurable outcomes, following proven PM frameworks.

Problem Discovery

    Utility companies face high operational and regulatory risk from unmanaged vegetation near power lines. Traditional inspection methods—manual patrols, aerial surveys, or reactive reporting—are slow, expensive, and prone to error.
    We validated the opportunity through:
  • Interviews with utility field managers and operations teams
  • Quantitative analysis of outage data linked to vegetation
  • Feedback from early pilot programs showing risk predictability gaps

Business Alignment

  • Strategic Positioning: Establish AiDash as a satellite-first platform for utility asset intelligence
  • Revenue Model: Subscription-based SaaS, targeting large utility and infrastructure firms
  • Efficiency Goals: Replace manual inspection with automated satellite analytics to reduce cost and inspection frequency
  • Growth: Support cross-functional deployment across asset management, compliance, and sustainability teams

Solution Exploration

We considered multiple approaches: drone-based visual analysis, manned aerial surveys, and a remote-sensing platform. Based on scalability and cost-effectiveness, we prioritized satellite-powered analytics.

    MVP Feature Set:
  • Satellite-driven vegetation risk scoring
  • AI models to identify encroachment risk zones
  • Work order generation based on severity and location
  • Integration with enterprise asset management (EAM) systems
  • Dashboards for operations and compliance tracking

Execution

    As PM, I collaborated with:
  • Design: To map the utility operations workflow from satellite detection to field dispatch
  • Engineering: To develop scalable cloud pipelines, REST APIs, and AI model integrations
  • Partner Utilities: For beta testing and feedback loops
  • Customer Success: To align deployment timelines with vegetation management cycles
    • We aligned with GIS leads and IT departments to ensure data integration didn't disrupt existing workflows.

Outcomes & Impact

Impact:
  • Reduced vegetation-related outages by 20% in pilot deployments
  • Lowered inspection costs by 30–40%
  • Improved audit traceability and regulatory readiness for customers
Learnings:
  • Integration is as important as prediction—without syncing to EAM systems, value delivery stalls
  • Customization by vegetation type, climate zone, and utility operating model increased adoption
  • Risk-based prioritization shifted organizations from time-based to outcome-driven inspections

Project Artifacts

Supporting materials, frameworks, and deliverables created during the product development process.

Vegetation Risk Dashboard

image

Satellite-powered dashboard for utility vegetation risk scoring

EAM Integration Guide

document

Documentation for integrating IVMS with enterprise asset management systems

These artifacts demonstrate the systematic approach to product development, from initial discovery through execution and measurement.