What is Chat Summary for LiveChat?

Chat Summary is an AI‑powered tool that integrates with LiveChat to generate concise summaries from chat transcripts. It uses OpenAI’s natural language processing to extract key points, keywords, and sentiment from each conversation. The app automatically creates summaries when chats are archived or tagged, with an option to generate them manually from the details panel.

Centralized reporting lets agents review all summaries along with chat ID, thread ID, and full transcripts in one place. Sentiment analysis highlights emotional tone and critical discussion topics, while actionable agent feedback provides insights to improve customer interactions.

Chat Summary for LiveChat on the web:

Chat Summary for LiveChat details

Company: Text, Inc.
Jurisdiction: Massachusetts, United States of America
Built for: Individuals
Data residency: United Kingdom

Chat Summary for LiveChat tech specs

Works with: OpenAI / GPT
Integrations: Shopify WhatsApp

Chat Summary for LiveChat pricing

Free trial

Starter $19

Team $49

Chatbot $52

Business $79

Enterprise call

$1.67/mo is cheaper than most for Customer support median $28.50/mo

Most Customer support tools start between $11.75 and $63.75 a month.

Free trial: 14 days
Auto-renewal: Yes

Trial, refund and renewal terms as stated in Chat Summary for LiveChat's own published documentation.

Verify on the official pricing page.

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Chat Summary for LiveChat's key features

AI-driven chat automation
Multi-channel messaging (SMS, WhatsApp, Facebook)
Real-time chat widget customization
Integration with 200+ apps
Comprehensive analytics & reporting
Secure data storage & encryption
Bot creation and knowledge base

Chat Summary for LiveChat use cases

Generate real-time post-chat summary reports for each LiveChat session, highlighting key customer issues and sentiment trends to enable managers to quickly address recurring problems
Automatically extract actionable agent feedback from chat transcripts, scoring performance and providing targeted training recommendations based on sentiment and keyword analysis
Create a centralized archive of summarized chat interactions, allowing teams to search key topics and metrics across thousands of conversations without sifting through raw transcripts