Dedomena offers a comprehensive platform designed to empower utility companies with advanced AI capabilities and synthetic data. Our solutions are specifically tailored to address the unique demands and challenges faced by the Utilities sector, including asset optimization, grid management, customer engagement, and energy forecasting.
The Utilities industry thrives on data-driven
insights to fuel growth, innovation, and streamlined
operations. However, the fragmented nature of data
sources, stringent privacy regulations, and
cybersecurity concerns often impede the industry's
ability to fully capitalize on its data wealth.
Dedomena's synthetic data solutions provide a
game-changing approach for Utilities, enabling the
creation of high-quality synthetic data sets that
adhere to privacy regulations while accurately
reflecting the intricacies of the industry. By
leveraging our synthetic data, Utilities can
surmount data fragmentation, achieve compliance, and
accelerate the development of AI/ML models, software
testing, and data-driven initiatives.
Our synthetic data solutions empower Utilities to
wield precise and anonymized synthetic data sets,
amplifying asset optimization strategies, enhancing
grid management precision, fueling superior customer
engagement, and enabling data-driven decision-making
with unwavering confidence.
The utilities sector faces growing pressure to modernize, improve resilience, and meet regulatory demands amid the rise of AI, smart meters, and IoT. Dedomena.AI’s synthetic data and AI platform enables secure insight generation, performance optimization, and data sharing. Below are 20 essential use cases where Dedomena.AI drives digital transformation and sustainable intelligence across the utilities industry.
Dedomena.AI generates synthetic electricity, gas, and water consumption data to train models for forecasting demand and analyzing customer behavior.
Create synthetic load profiles and weather-influenced demand patterns to optimize electricity distribution and prevent overloads.
Model normal and irregular usage behavior to train fraud detection systems that identify meter tampering, theft, or leaks.
Simulate fault event logs and equipment data to train AI models that predict outages and optimize dispatch of response crews.
Generate synthetic consumer response data to test incentive models for reducing peak demand in electricity or gas networks.
Model pipe system telemetry with synthetic flow, pressure, and sensor data to identify hidden leaks and infrastructure degradation.
Use synthetic solar, wind, and consumption data to train forecasting models for renewable integration and storage management.
Simulate structured customer feedback, billing, and service usage to build models for churn risk scoring and engagement planning.
Dedomena.AI enables simulation of building-level efficiency metrics to model impacts of insulation, retrofitting, or renewable incentives.
Train pricing models using synthetic usage and customer profiles to test tariff sensitivity and build fair, personalized pricing plans.
Generate synthetic DER activity data to simulate impacts on local grid performance and plan DER-friendly load management strategies.
Create synthetic vehicle charging patterns across regions to optimize station placement, grid planning, and peak load distribution.
Simulate structured support logs to train AI assistants for billing inquiries, outage reporting, or account management.
Develop synthetic intrusion patterns and device logs to build and test anomaly detection systems against cyber threats.
Model capital investment scenarios using synthetic geospatial demand and infrastructure health data to prioritize modernization projects.
Simulate collection patterns, bin fill levels, and fleet telemetry to optimize scheduling and fuel usage for sanitation services.
Generate synthetic data aligned with reporting schemas to test audit readiness, simulate ESG disclosures, and automate compliance checks.
Model synthetic consumption patterns across building types to support energy ratings, LEED scoring, and sustainability programs.
Enable privacy-compliant sharing of operational, consumption, and customer data with vendors, regulators, or municipal partners.
Combine synthetic asset telemetry with LLM-based copilots to assist grid operators and asset managers in forecasting, diagnostics, and decision support.
Check out some of our explanatory articles or
cross-industry
use cases to know more
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