GridGuard provides an AI‑driven platform that automates fault diagnosis for transmission and distribution utilities, using machine‑learning pattern recognition and impedance calculations on SCADA data to pinpoint fault type and location within minutes.
Funding
Funding not disclosed
Founders
Product
Problem
Utility engineers spend a large portion of their time manually analyzing SCADA data and compiling compliance paperwork after grid outages, leading to slow fault location (often 4–6 hours) and inconsistent diagnostic quality. This manual process also creates a heavy burden of NERC documentation, increasing the risk of errors and higher engineering costs.
Solution
GridGuard offers an AI-driven platform that automates fault diagnosis by applying machine‑learning pattern recognition and impedance calculations to SCADA data, delivering precise fault type and location within minutes. The system generates audit‑ready NERC compliance reports and detailed repair PDFs automatically, eliminating repetitive health checks and paperwork. Continuous real‑time monitoring provides instant alerts and prioritizes events for rapid response. By streamlining analysis and documentation, GridGuard reduces engineer time on fault analysis by up to 40% and cuts planning‑and‑construction engineering costs by roughly one‑third, while enhancing overall grid reliability.
Target Audience
Primary customers are transmission and distribution utility operators and their planning‑and‑construction engineering teams responsible for outage response, fault analysis, and regulatory compliance.
Features
- Machine‑learning analysis of SCADA streams combined with impedance calculations for fast, accurate fault identification
- Automated step‑by‑step diagnostic workflow that produces traceable, NERC‑CIP compliant documentation
- Instant alerting and priority‑based event queuing for real‑time grid health monitoring
- One‑click generation of comprehensive PDF reports with root‑cause analysis, repair recommendations, and compliance evidence
- Enterprise‑grade data security and audit trails to meet utility regulatory standards
- Built‑in scalability for large utility networks with continuous data ingestion and processing