Solving the AI accuracy problem for Product Support | November 20th at 3 pm ET / 12 pm PT | Register Here

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GenAIChatbot

With Agolo’s trusted knowledge graph, GenAI chatbots provide more precise and accurate answers to customers – leading to lower product support costs and higher customer satisfaction

Use Cases

Improve GenAI chatbot accuracy

Current Challenges: This consumer electronics company that designs, sells and supports monitors and televisions built a chatbot powered by Generative AI.  While accurate for roughly 60% of questions, the AI assistant made mistakes in the remaining 40%. The wrong answers were a mix of "hallucinations" and "incomplete answers." As context, industry benchmarks cite hallucinations ranging from 3% to 27% based on query type, complexity, and LLM.
To address this issue, the organization looked to a solution to fine-tune the underlying LLMs that power the application.

  • Agolo Solution: Agolo delivers relevant and accurate information by understanding your customers’ issues, products, people, and their relationships. Leveraging Agolo’s GenAI-powered knowledge graph will supercharge any GenAI chatbot and digital assistant, enabling customers to resolve their issues faster and more easily.

  • Business Value: With Agolo’s trusted knowledge graph, this company’s GenAI chatbot provided more accurate answers to customers. Users were able to resolve more of their issues through the chatbot. Adoption rates of the bot increased over time, shifting traffic away from higher cost channels, including voice and email, leading to lower support costs.  Industry case studies show that Generative AI-based chatbots can handle up to two-thirds of customer inquiries, while also reducing repeat inquiries by 25% and maintaining customer satisfaction.