March 10, 2026

Rhizome Deploys AI-Powered Grid Planning Solution for Horizon Networks in New Zealand

Rhizome is deploying its gridADAPT platform with Horizon Networks, a New Zealand electricity distribution utility, to strengthen grid resilience across more than 8,000 square kilometers of infrastructure in the Eastern Bay of Plenty region.

Read Horizon's press release here.

The Challenge

Climate change is fundamentally reshaping how utilities around the world plan and invest in grid infrastructure. For Horizon Networks—a 100% locally owned utility serving approximately 25,500 homes and businesses in New Zealand’s Eastern Bay of Plenty region—this challenge is immediate and intensifying.

Research from NIWA confirms that the Eastern Bay of Plenty will continue to experience increasingly severe weather driven by climate change, putting pressure on grid infrastructure that was never designed to withstand these conditions. As climate variability accelerates, utilities need tools that can quantify future risk and translate it into defensible, cost-effective investment decisions—while ensuring prudent use of ratepayer funds.

How gridADAPT Works

gridADAPT uses machine learning to analyze climate risk patterns, asset vulnerability, and network performance data, enabling utilities to develop evidence-based, forward-looking investment plans. By combining climate projections with infrastructure characteristics, gridADAPT provides unprecedented visibility into future risks—helping utilities balance reliability, resilience, and cost-effectiveness.

This deployment will enable Horizon Networks to:

  • Enhance distribution planning processes with AI-driven climate risk analysis
  • Optimize investment strategies in response to increasing climate variability across the Eastern Bay of Plenty region
  • Develop cost-effective capital allocation decisions that address both immediate reliability needs and long-term climate resilience
  • Demonstrate the value of machine learning tools in utility planning to regulators and stakeholders

What This Means for Rhizome

This partnership reinforces that AI-driven grid resilience planning delivers value across all geographies and network types. The deployment received Innovation and Non-Traditional Solutions Allowance approval from the New Zealand Commerce Commission, reflecting growing regulatory recognition of machine learning tools in utility capital planning.

Working with Horizon Networks—a utility navigating a distinct regulatory environment and climate context—validates gridADAPT’s capability to support utilities of varying scales with geographically specific challenges. This follows Rhizome’s recent partnership with National Grid across the United Kingdom, Massachusetts, and New York, further demonstrating the platform’s applicability from the Northeast United States to the South Pacific.

“Climate change is fundamentally altering how we plan and invest in grid infrastructure. Rhizome’s technology will allow us to make more informed decisions about where and how to deploy capital to build a more resilient network for our customers.”
— Ajay Anand, Chief Executive, Horizon Energy Group

“Utilities everywhere are facing climate risks their infrastructure was never designed for. Today’s partnership with Horizon Networks puts them one step ahead of those impacts, keeping the lights on for their customers.”
— Mishal Thadani, Co-Founder and CEO, Rhizome

Looking Ahead

As extreme weather events increase in frequency and severity worldwide, utilities need tools that help them anticipate and address climate-driven threats before they impact customers. gridADAPT provides the quantitative foundation for those decisions, helping utilities optimize capital expenditure while building resilience against an uncertain climate future.

The Horizon Networks deployment will be trialed over the next twelve months. Since launching its platform in 2023, Rhizome has engaged in utility partnerships spanning North America, Europe, and now the South Pacific, with mission-specific tools including gridFIRM, gridCAVA, and gridADAPT.

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