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Utility Data Intelligence: AI-Driven Outage Prevention

DATAFOREST provides utility data services by creating tailored Customer Data Platforms (CDPs) and other AI solutions for utilities to integrate and manage diverse utility data, build scalable cloud data lakes, and optimize data pipelines. We leverage utilities data analytics to deliver insights and implement Generative AI for automating reporting and customer service interactions.

Let your data create value

Utility Data Services_ From Reactive to Predictive Operations

AI-Powered Utility Data Solutions

Through these services and with the integration of generative AI in utilities, we transform operations from reactive to predictive by leveraging predictive analytics for utilities that prevent outages, optimize resource allocation, and enhance the customer experience.

Predictive Maintenance

Equipment failures are predicted days in advance using pre-trained models that analyze utility data collection from transformers and pumps. This reduces unplanned outages by 20-30% within the first quarter while minimizing costly overtime and regulatory penalties.

Unified Data Lake & Integration Hub

Siloed systems, such as SCADA, CIS, and AMI, are connected through automated data pipelines to form a single cloud-based utility system or data source. Teams gain unified access to all operational utility data while reducing manual data preparation time by over 70%.

AI-Driven Demand & Load Forecasting

Machine learning models account for solar, EV charging, and weather variability to deliver precise 15-minute forecasts at the feeder level. Day-ahead accuracy improves by 30-40% while reducing expensive reserve scheduling costs.

Cross-Platform Crew & Work-Order Optimizer

Utilities AI agent routing and real-time visibility replace paper-based work orders with intelligent dispatch optimization. Truck rolls and overtime decrease by up to 25% while significantly reducing repair response times.

AI-Powered Customer Service Agent

AI chatbots for utilities and GenAI agents handle routine inquiries about outages, as well as AI-powered bill reading, utilizing utility bill data and specific training inputs. These systems deflect 40-60% of Tier-1 calls while improving customer satisfaction without additional staffing.

AI Readiness & 2-Week PoC Accelerator

Custom proof-of-concepts demonstrate real AI for utility applications, such as anomaly detection or chatbots, within 14 days. Leadership gains concrete ROI insights to secure budgets and develop realistic AI implementation roadmaps.

Self-Service Web & Analytics Portal

Modern, mobile-friendly portals replace legacy utility information systems with embedded business intelligence and dashboards for real-time utility data monitoring. Digital adoption increases while call center volumes and operational costs decrease.

Utility Data Management Services and Solutions Benefits

Stop guessing when equipment will fail, end the spreadsheet nightmare, and let AI handle the tedious tasks so your team can focus on what matters.

AI in utilities identifies failing transformers and pumps days in advance, allowing time for proper repairs.

I want it!

One platform consolidates everything, so analysts no longer need to copy and paste CSV files for structured data extraction and utility data analysis.

I want it!

Machine learning handles the chaos better than your current models ever will.

I want it!

Utilities AI maps the shortest routes, reducing wasted fuel and overtime pay.

I want it!

An AI chatbot for utilities handles the easy tasks, allowing humans to focus on more pressing issues.

I want it!

Modern portals let customers solve their own problems instead of calling you.

I want it!

Automated systems generate what regulators want without the manual headache.

I want it!

Two-week tests show real results before you commit serious money.

I want it!

Your utility data lives in different places, and none of them talk.

Fix the mess. Stop the spreadsheet circus.

Get in Touch

Accurate Utility Data Management Cases

Check out a few case studies that show why DATAFOREST will meet your business needs.

All Success Stories

Generative AI

Digital

Data Insights & Forecasting

Reporting & Analysis Automation with AI Chatbots

The client, a water operation system, aimed to automate analysis and reporting for its application users. We developed a cutting-edge AI tool that spots upward and downward trends in water sample results. It’s smart enough to identify worrisome trends and notify users with actionable insights. Plus, it can even auto-generate inspection tasks! This tool seamlessly integrates into the client’s water compliance app, allowing users to easily inquire about water metrics and trends, eliminating the need for manual analysis.

100

of valid input are processed

insights delivery

View case study

Automating Reporting and Analysis with Intelligent AI Chatbots

Pharma

Digital Transformation

Business process automation

AI Platform Revolutionizing Healthcare Insights

A UK healthcare market intelligence company partnered with Dataforest to drive digital transformation. We developed an AI-powered enterprise management platform that automated core processes such as data collection and report generation with deep analytical insights. With dynamic web scraping, AI-based deduplication, and GenAI data enrichment, the solution cut 9,600+ manual hours monthly and doubled productivity—delivering significant operational gains.

9,600

hours/month of manual work eliminated

increase in overall productivity

View case study

AI Platform Revolutionizing Healthcare Insights

Web and mobile development

Business process automation

Healthcare

Back Office Automation

The client faced the challenge of upgrading their legacy manual and offline processes to new digital and emerging technologies and wanted to change the way suppliers, customers, and contractors interact with each other and improve their delivery process. The solution we implemented was a tailor-made web application that digitized the entire business process - CRM, warehouse management, and product delivery tracking.

FTE costs reduction

revenue growth

Aleksandr Kharin

CEO Biolevox, Medical Product Distributor

View case study

They immediately understood needs and expectations and assembled an excellent team to ensure the project is delivered on time and within budget. They remain very flexible and responsive.

All Success Stories

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Technologies For the Utility Data Services

Pandas

SciPy

TensorFlow

Numpy

ADTK

DBscan

G. AutoML

Keras

MLFlow

Natural L. AI

NLTK

OpenCV

Pillow

PyOD

PyTorch

FB Prophet

SageMaker

Scikit-learn

SpaCy

XGBoost

YOLO

Steps Toward Utility Data Intelligence

These data engineering development stages ensure that solutions are well-designed, thoroughly tested, and aligned with business objectives.

How do we help companies?

Step 1 of 7

Initial Project Assessment and Definition

In the early phases of our data engineering development process, we engage in a free consultation to gauge project compatibility. During the discovery and feasibility analysis, we adapt to your needs, whether it's high-level requirements. We gather information to define project scope through discussions, including feature lists, data fields, and solution architecture. We craft a project plan to guide our progress, reflecting our dedication to achieving project goals and delivering effective data engineering solutions.

Step 2 of 7

Discovery

So, you have finally decided that you are ready to cooperate with DATAFOREST.

The discovery stage involves delving into the details of the project. Data engineers gather requirements, analyze existing data systems, and understand the needs of the business. This step is crucial for laying the groundwork for development, as it ensures that the project aligns with business goals and user needs.

Step 3 of 7

Tech Design and Backlog Planning

In this stage, the technical architecture and design of the solution are formulated. Data engineers plan how data will be collected, stored, processed, and presented. Simultaneously, the project backlog is created — a list of tasks and features to be developed. This backlog is prioritized, ensuring that high-priority items are addressed first.

Step 4 of 7

Development Based on Sprints

Development takes place in iterative cycles known as sprints. During each sprint, the development team tackles tasks from the backlog. The team focuses on coding, testing, and integrating the components. At the end of each sprint, a functional part of the solution is ready for review.

Step 5 of 7

Project Wide QA

Quality Assurance is an ongoing process that permeates the entire project development lifecycle. It ensures rigorous testing, identification, and resolution of any bugs or issues to guarantee the solution's smooth operation, compliance with requirements, and alignment with quality standards. The solution is prepared for release as QA activities persist and necessary adjustments are continuously implemented.

Step 6 of 7

Deployment and Rollout

The deployment phase involves releasing the solution to the production environment, making it accessible to users. It requires careful planning to ensure a seamless transition and minimal disruption. After deployment, the rollout phase begins, involving training for users and ongoing support to address any hiccups.

Step 7 of 7

Support and Continuous Improvement

In the final stages, we ensure ongoing excellence. We guarantee optimal performance and swiftly address any issues. Simultaneously, our feedback process empowers us to continuously enhance the solution based on user insights, aligning it with evolving needs and driving continuous innovation.

Articles About Utility Data Services

All publications All publications

May 21, 2025

19 min

The Importance of Data Analytics for Businesses at Every Stage of Growth

May 2, 2025

11 min

ERP Solutions Company: Tailored Integration for Business Intelligence

January 29, 2025

24 min

Predictive Maintenance in Utility Services: Sensor Data for ML

May 21, 2025

19 min

The Importance of Data Analytics for Businesses at Every Stage of Growth

May 2, 2025

11 min

ERP Solutions Company: Tailored Integration for Business Intelligence

January 29, 2025

24 min

Predictive Maintenance in Utility Services: Sensor Data for ML

FAQ On Utility Data Management

Can you help us reduce unplanned equipment downtime and maintenance costs?

We build predictive analytics for utilities that flag failing equipment 3-7 days early. This works for transformers, pumps, and generators if you have decent sensor data and consistent utility data collection. You'll still have failures, but fewer surprises and less overtime pay.

How can DATAFOREST optimize our workforce scheduling for 24/7 power generation operations?

We create scheduling algorithms that balance crew availability, skills, and travel time. The system handles shift changes, emergency calls, and maintenance windows. Your dispatchers get better visibility and control, but they still make the final calls.

Can your analytics help us maximize revenue in deregulated energy markets?

We build forecasting models for price arbitrage and demand response programs. The models spot profitable trading windows and optimize generation dispatch. Energy usage optimization and markets are unpredictable, so expect modest improvements, not miracles.

How long does it typically take to implement your Fleet Management System for our generation assets?

Implementation takes 12-16 weeks for most utilities. This includes utilities, AI data management, testing, and training your team. Complex legacy systems or poor data quality can add 4-8 weeks to the project timeline.

Can you integrate data from our existing SCADA systems, smart meters, and maintenance databases to create a comprehensive view of our operations?

We connect these systems through digital utility solutions and automated pipelines. The utility data is uploaded to a unified energy data platform within 8-12 weeks. Expect some cleanup work if your historical data has quality issues.

What types of dashboards and reports do you provide for utility operations management?

We build custom dashboards for outage tracking, equipment health, and crew performance. Reports cover regulatory compliance, maintenance schedules, and financial metrics, including utility finance and accounting. Everything updates in real-time, assuming your data feeds work properly.

Can your customer usage analytics help us reduce energy theft and improve billing accuracy?

Our algorithms identify unusual consumption patterns in energy data intelligence and utility bill data that indicate potential theft or metering issues. You'll catch more issues, but investigation and enforcement are still manual processes. Expect to find 2-5% more revenue in most cases.

Can you help us optimize our energy trading strategies and reduce market risks?

We build models that forecast prices and identify arbitrage opportunities. The system suggests optimal trading positions based on your risk tolerance and investment goals. Cost modelling is part of these strategies. Markets move fast, so human traders still make the final decisions.

How can we get started with ordering utility data analytics services from DATAFOREST?

Request a meeting. We'll discuss your utility industry issues. Next, we check your data. Then, we build a custom plan. This includes data analytics for utilities, custom work, and AI, leading to more natural utilities. Finally, we build and deliver it. We'll support it and make improvements.