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.
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.
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.
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%.
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.
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.
Predictive Maintenance
Unified Data Lake & Integration Hub
AI-Driven Demand & Load Forecasting
Cross-Platform Crew & Work-Order Optimizer
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.
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.
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.
AI-Powered Customer Service Agent
AI Readiness & 2-Week PoC Accelerator
Self-Service Web & Analytics Portal
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.
01 AI in utilities identifies failing transformers and pumps days in advance, allowing time for proper repairs.
05 An AI chatbot for utilities handles the easy tasks, allowing humans to focus on more pressing issues.
02 One platform consolidates everything, so analysts no longer need to copy and paste CSV files for structured data extraction and utility data analysis.
06 Modern portals let customers solve their own problems instead of calling you.
03 Machine learning handles the chaos better than your current models ever will.
07 Automated systems generate what regulators want without the manual headache.
04 Utilities AI maps the shortest routes, reducing wasted fuel and overtime pay.
08 Two-week tests show real results before you commit serious money.
Steps
Towards Good Development
These data engineering development stages ensure that solutions are well-designed, thoroughly tested, and aligned with business objectives.
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.
Initial Project Assessment and Definition
1
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.
Tech Design and Backlog Planning
3
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 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.
2
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Development Based on Sprints
4
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.
Deployment and Rollout
6
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.
Project Wide QA
5
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.