Smart grid and big data company Delta Energy has launched QORTEX™, an agentic AI platform designed to help utilities convert fragmented operational data into predictive and actionable intelligence.

Now available, QORTEX is designed to be a cognitive operating layer for the modern grid, integrating information from systems such as SCADA, AMI, GIS, OMS, CIS, weather services, asset management platforms, and other operational technologies into a single, unified view of utility operations.

The platform aims to address the challenges utilities face today, especially as aging infrastructure is becoming increasingly difficult and expensive to maintain. Electrification and rapid data center growth are driving unprecedented demand on the grid, according to Delta Energy. Additionally, severe weather, wildfire risk, and evolving regulatory requirements are forcing operators to make faster, more complex decisions with greater accountability. Yet many utilities are still managing these challenges through a patchwork of disconnected systems and manual processes, the company noted.

Rather than replacing existing infrastructure, QORTEX is designed to work across current systems to continuously identify risks, surface recommendations, and provide operators with the context needed to make faster, more informed decisions.

“From the control room to the boardroom, QORTEX aligns every level of your operation. Operators gain precise situational awareness; field crews deploy targeted intelligence; and executives receive performance-driven insight tied directly to reliability, cost control, and risk reduction,” said Everardo Camacho, CTO at Delta Energy.

Delta Energy CEO Scott Foster added that whether investor owned utilities (IOUs) or regional co-ops, when it comes to grid management, there is a need to move enterprise AI from back-office efficiency to mission-critical infrastructure. “QORTEX sits across existing infrastructure rather than replacing it, unifying fragmented data into one decision layer with full audit-ready governance,” Foster said.

As utilities work to improve reliability and resilience, QORTEX aims to provide practical, day-to-day operational value across multiple areas of the business. For example, during periods of elevated wildfire risk, QORTEX can continuously evaluate weather forecasts, vegetation data, equipment health, historical outage patterns, and real-time grid telemetry to identify emerging risk zones. The platform generates dynamic risk scores and provides operators with clear recommendations that support operational decision-making and regulatory compliance, according to the company.

QORTEX also aims to help utilities prioritize infrastructure investments by identifying assets that present the highest reliability or safety risks, to enable more strategic capital planning and improved resource allocation. For customer service and regulatory teams, QORTEX was designed to create a complete, auditable record of recommendations, supporting rate cases, compliance reporting, and post-event analysis, Delta Energy said.

QORTEX’s capabilities:

• Unified operational intelligence: The platform is designed to unify data from SCADA, AMI, GIS, CIS, OMS, weather platforms, asset management systems, and other utility technologies into a single operational view.
• Proactive risk detection: It was created to identify emerging reliability, safety, and wildfire risks before they escalate into outages or regulatory events.
• Human-guided AI: The system can provide recommendations and intelligence while maintaining full operator control over utility systems.
• Audit-ready decision support: It creates complete records of recommendations, data sources, and decision pathways to support compliance, regulatory reporting, and governance requirements.
• Rapid deployment: It integrates with existing utility infrastructure without requiring system replacement, enabling deployment in weeks rather than years.
• Scalable, predictable pricing model: Per-meter pricing allows utilities to scale adoption predictably as operational needs evolve.