Intelligent Automation and RPA in Utilities and Energy Operations

IA and digital workers streamline customer interactions by gathering real-time information to address inquiries, such as billing updates. By leveraging Natural Language Processing (NLP), they can understand and respond to common queries, update records, and initiate follow-ups effortlessly.

Digital workers facilitate consistent and proactive customer engagement, delivering payment reminders, personalised offers, and notifications about rate changes. This approach keeps customers informed and enhances overall service quality.

Automate account activation and deactivation processes, and synchronise customer records across multiple systems. Regular outreach automation ensures that customers are kept informed of their progress while maintaining compliance with industry standards.

Enhance the speed and effectiveness of customer interactions across various channels, resulting in quicker resolutions, reduced costs, and memorable customer experiences. Quickly assess customer needs and allocate resources effectively to meet those demands.

Improve operational efficiency and accelerate failure prediction by integrating AI and Machine Learning (ML) predictive maintenance models into everyday systems, leading to increased equipment uptime and reduced operational costs.

Automate the scheduling of regular maintenance and safety checks, including necessary rescheduling based on field reports.

Enable engineers to update asset records in the field, automatically syncing changes with multiple back-office systems to maintain accuracy, consistency, and adherence to Service Level Agreements (SLAs).

Monitor inventory levels against actual stock to automatically generate purchase orders for suppliers. This approach speeds up the procurement process and mitigates delays.

Automate the collection of metre readings from various sources, including smart metres, customers, third-party readers, and estimates.

Intelligent Automation enhances billing accuracy by investigating discrepancies in metre readings from multiple sources. This proactive approach helps prevent erroneous bills and improves customer satisfaction by automatically verifying reliable reading sources and correcting billing systems.

Intelligent Automation can identify accounts with excessive or negative consumption, correcting errors or requesting additional information as needed.

Integrate legacy billing systems with third-party mobile payment applications, allowing customers to make payments effortlessly. Digital workers streamline this process by updating core billing systems with payment data, ensuring accurate reconciliation without manual intervention.

Collection agents can submit updates on the status of visits, whether successful or not. Digital workers automate the updating of relevant systems, saving time and eliminating manual data entry errors.

Intelligent Automation assists in compiling customer information—such as searching credit record websites — prior to collection actions. This automated validation reduces manual effort and minimises wasted agent time on unnecessary visits.