Conversation Summarization

Summarizes prior customer conversations so support agents can pick up cases faster with context.

Business impact

• Information-search speed — AT&T reported customer-care agents were 33% faster at information searching.
• System language coverage — Expedia Group’s system supports more than 30 languages.

Data requirements

• Customer conversation transcripts (text) — Used to generate summaries of prior interactions.
• Call transcripts (text) — JPMorgan Chase reports summarizing call transcripts in contact-center work.
• Customer history and context records (tabular) — AT&T’s deployment retrieves customer context and verified information for agents.
• Support tickets (text) — Shopify’s workflow includes ticket summarization and case review.

AI methods and techniques

• Conversation summarization — The core function is to condense earlier customer exchanges into a short readable summary for support staff.
• Information retrieval — In AT&T’s deployment, AI retrieves verified information and customer context for the representative.
• Call transcript summarization — JPMorgan Chase reports summarizing call transcripts in its contact-center workflow.
• Ticket summarization — Shopify’s reported workflows include summarizing support tickets for internal review.

AI models and model families

Azure OpenAI, LLM Suite, Gumloop

Industries

Real-world evidence

5 documented case studies on record.

Companies using this: AT&T, Expedia, JPMorgan Chase, LVMH, Shopify.