Next Level CX: Agentic AI from Inbox to Resolution

In this session, Power Reply will demonstrate a practical Agentic AI workflow that addresses one of the most persistent challenges in utility customer service: the slow, manual path from incoming customer inquiries to resolved service cases.

What makes customer service slow today:

•    Customer requests arrive across multiple channels (email, chat, phone, self-service portal) and in different languages
•    Utility-specific inquiries – meter readings, billing questions, budget billing changes, bank data updates – require manual reading, classification, and spam-checking before processing can even begin
•    Relevant business data (contract accounts, meter numbers, meter reading dates) must be extracted manually from unstructured messages
•    Manually searching the knowledge base and drafting individual responses consumes significant agent time
•    Recurring, high-volume cases – the bulk of a company's daily inbox – occupy capacity needed for genuinely complex ones
•    Response times suffer and service quality varies with workload, language, and agent experience


We have built the Power AI Service App, a system of autonomous AI agents purpose-built for utility customer service that:
•    Classifies incoming requests – detects spam, category, language, and sentiment across all channels
•    Extracts relevant business data – pulls parameters such as contract accounts, meter readings, and meter reading dates directly from customer messages
•    Summarizes and translates – condenses each case and translates foreign-language emails for the agent
•    Answers questions using an intelligent knowledge base – retrieves accurate, consistent answers grounded in existing documentation instead of relying on manual lookups
•    Executes standard utility processes autonomously – books meter readings, adjusts budget billing amounts, and creates bank data directly in SAP S/4HANA and SAP IS-U
•    Keeps the agent in full control – every agentic step is transparent and documented, with human review built in before any email is sent

This session features a live demo: a customer's meter-reading email moves through all six process steps – inbound capture, spam-check and classification, data extraction, backend booking in SAP, AI-generated response drafting, and agent-reviewed dispatch – with no break in the SAP process chain. While built around the specific process patterns of energy and utility providers, the underlying agent architecture applies equally to any organization handling high-volume, multi-channel customer service.