AI for Smarter Energy Data – Understanding Household Needs in Real Time

AI for Smarter Energy Data – Understanding Household Needs in Real Time

kraftringen AI för smartare energidata – förstå hushållens behov i realtid

Kraftringen + Softhouse – Data-Driven Customer Insights with AI

To offer more relevant services and optimize grid operations, Kraftringen set out to better understand household energy usage. Do customers have an electric vehicle? A heat pump? Using sequential data from energy consumption, we partnered to develop an AI-based solution that classifies household energy profiles—without the need for manual input.

By training a machine learning model on real consumption data, we were able to detect patterns that reveal which energy-intensive appliances are in use. This enables a more accurate understanding of each customer’s needs.

What we did

  • Leveraged sequential energy data to predict the presence of EVs and/or heat pumps

  • Trained a high-accuracy AI model without relying on external sensors

  • Built a foundation for future AI initiatives within the organization

Business impact

With a deeper understanding of customer energy behavior, Kraftringen can:

  • Tailor services and offerings based on actual usage

  • Insights that can help better optimize grid operations and capacity planning.

  • Enable proactive communication and sustainability efforts

This project clearly shows how AI and energy data can come together to create value—for utilities and their customers alike.

We code the future – one kilowatt at a time.

Share this
Share this
Share this
Share this

  • From Machine Learning Pioneers to the Future of AI Solutions

  • Officebot – AI That Knows Your Employee Handbook

Project Details

What? Develop an AI-based solution to analyze household energy consumption and classify the presence of electric vehicles and/or heat pumps – supporting better customer insights and optimized grid operations.

Organization: Kraftringen Energi AB

Industry: Energy / Power Supply / Sustainability-Driven Digitalization

Number of Employees: Approximately 300

Revenue: Approx. SEK 2.5 billion (2023)

Technologies and Methods: Machine Learning, AI, Sequential Data Analysis, Classification Models, Energy Statistics, Customer Segmentation, AI-Powered Insight Generation

  • Machine learning

    Machine learning is a branch of AI where computers learn from data to make decisions or predictions without being explicitly programmed. It’s used in everything from recommendation systems to image recognition and predictive analytics.

  • AI

    AI (Artificial Intelligence) is a broad term for technologies that enable computers to mimic human thinking—such as analyzing information, making decisions, and learning from experience. AI is used in everything from chatbots to advanced industrial automation.

  • Sequential data analysis

    Sequential data analysis involves analyzing data in chronological order—such as energy consumption over the course of a day—to identify patterns, trends, or anomalies. It’s commonly used in areas where behavior changes over time, such as energy management and user behavior analysis.

  • Classification models

    Classification models are a type of AI model that sort data into categories based on previously learned patterns. For example, they can be used to determine whether a household has an electric vehicle based on its energy consumption.

  • AI-powered insight generation

    AI-powered insight generation involves using AI to automatically detect patterns in large datasets and transform them into actionable business insights. It helps organizations respond faster and make more data-driven decisions.

We code the future

We’re committed to shaping the future through innovative coding solutions and beautiful experiences.