Minerva CQ Launches LLM Specific to EV Charging

Minerva CQ, a provider of real-time collaborative artificial intelligence, has launched an emobility large language model (LLM) for electric vehicle (EV) charging customer service.

EV customers calling about issues with charging stations, installation, billing, and mobile apps can now be helped by contact center agents guided by AI specifically built to understand customer conversations, journeys, and intents in e-mobility.

Key features of the e-mobility LLM by Minerva CQ include the following:

• Natural language understanding that allows the LLM to interpret and comprehend customer inquiries specific to eMobility, regardless of their complexity or language nuances. These include customer issues with charging stations, installation, billing, and mobile apps to name a few.
• Retrieval augmented generation (RAG), which provides knowledge to agents from knowledge bases and external sources for Q&A and text summarization.
• Real-time support and data processing capabilities that allow the LLM to detect intent, entities, and sentiment to power workflows, dialogue suggestions, behavioral cues, and knowledge surfacing.
• Continuous learning through ongoing training and feedback mechanisms.

"With the growing number of commercial and residential EV charging stations, customer experience will be paramount as competiton intensifies," said Cosimo Spera, founder and CEO of Minerva CQ, in a statement. "Recognizing this need, Minerva CQ has developed a cutting-edge LLM capable of understanding and responding to a wide range of customer inquiries and troubleshooting issues so eMobility agents can resolve customer issues faster and with more confidence."