Client: H2O America
H2O America, a Tier 1 national water utility serving millions of customers across the United States, was sitting on vast amounts of untapped operational data — sensor telemetry from thousands of IoT devices, SCADA readings, GIS asset records, maintenance histories, and customer service logs spread across dozens of disconnected systems.
The utility needed to move from reactive, break-fix maintenance to a predictive model that could anticipate failures before they happened — improving service reliability, extending asset lifespans, and reducing the cost of unplanned outages. Veriland partnered with H2O America to build a unified data engineering platform and deploy AI-driven predictive maintenance across their critical infrastructure.
Water utilities manage some of the most critical infrastructure in the country, yet much of it is ageing and monitored by fragmented systems that were never designed to talk to each other. H2O America faced a series of interconnected data and operational challenges that were holding back their ability to deliver reliable, efficient service.
Veriland designed and delivered an end-to-end data engineering and AI platform that unified H2O America's operational data and turned it into predictive intelligence — enabling the utility to anticipate failures, optimise maintenance schedules, and deliver more reliable service to customers.
At the foundation, Veriland built a cloud-native data platform on Azure that ingests, transforms, and centralises data from every operational system — SCADA, IoT sensors, GIS, ERP, field service, and customer records. VeriConnect® handles the secure data movement between on-premise legacy systems and the cloud, using outbound-only agent connections that satisfy the utility's strict firewall policies. The platform processes over 5 million records per hour, creating a single unified data backbone for analytics and AI.
With clean, unified data flowing into the platform, Veriland's data science team built and deployed machine learning models that analyse asset telemetry patterns to predict failures before they happen. The models correlate sensor readings, maintenance history, asset age, environmental factors, and operational load to generate asset health scores and risk-ranked maintenance recommendations — shifting H2O America from reactive to predictive operations.
Rather than flooding field teams with raw sensor alerts, the AI layer correlates and deduplicates signals across the network, identifies genuine anomalies, and automatically generates prioritised work orders. This reduced alert noise by 5x while ensuring that early-warning signals of real failures are surfaced and acted on immediately.
The platform surfaces predictive insights through real-time dashboards that give operations managers, field supervisors, and executives a unified view of asset health, predicted failure timelines, maintenance schedules, and service reliability metrics — all drawn from the same trusted data layer.
The AI and data engineering platform transformed H2O America's operations from reactive to predictive, delivering measurable improvements across efficiency, service reliability, and asset management.
“For the first time, we can see a pipe failing before our customers notice. That shift from reactive to predictive has changed how we plan, how we budget, and how we serve our communities.”
“Veriland didn’t just connect our systems — they turned our data into something we can actually act on. The predictive models have paid for themselves many times over in avoided emergency repairs.”
The platform is built on Microsoft Azure with Veriland's data engineering expertise and proprietary integration technology at its core.
Azure Data Factory, Data Lake Storage, and Synapse Analytics providing the cloud-native data engineering foundation for ingestion, transformation, and analytics at scale.
Model training, deployment, and monitoring for predictive maintenance — generating asset health scores and failure predictions from unified telemetry data.
Veriland's proprietary secure agent-based platform handling data movement between on-premise legacy systems and the cloud — zero inbound firewall ports required.
Operational intelligence dashboards giving every level of the organisation visibility into asset health, predicted failures, and maintenance effectiveness.
