AI Summaries Overview
Bright Pattern Contact Center's AI Summary features use AI to generate concise and relevant summaries of customer interactions, improving the efficiency of agents, quality managers, and interaction analysts. AI Summaries are provided in two forms, although both are driven by a single, configurable summary template:
- Real Time AI Summary / Notes: Summarizes the agent-specific segment of the interaction to assist with after call work.
- Historical AI Summary: Summarizes the entire interaction to help managers and analysts performing reviews.
To get started with AI summaries in your contact center, refer to the AI Summary Quickstart for detailed instructions.
Real Time AI Summary / Notes (Per-Agent Segment)
Real Time AI Summary / Notes assist with After Call Work (ACW) by providing a summary specific to an agent's portion of an interaction. This summary is intended to complement or replace manual note-taking and speed up post-interaction tasks. Key elements of Real Time Summaries:
- Include only the segment of the conversation handled by a particular agent: For instance, if Agent A handles the initial part of a call and then transfers it to Agent B: Agent A (upon entering ACW) receives an AI-generated summary covering only their segment of the interaction up to the point of transfer. Subsequently, Agent B (upon entering ACW after their segment concludes) receives a summary for their own distinct segment.
- Presented in the Agent Desktop soon after ACW starts: Agents can copy the generated summary to their notes and edit it, which is useful when important information cannot be captured from the transcript (e.g., a CRM record was updated).
- Help agents prepare for upcoming interactions: Summaries appear in Activity History, allowing agents to review previous interactions from the same customer without needing to read the content of entire interactions.
Historical AI Summary (Entire Interaction)
Historical AI Summary give an overview of the entire customer interaction, including all agent segments. Managers and analysts can use this summary to assess the overall call or chat content, potentially reducing the need to review the full recording or transcript. Key elements of Historical AI Summaries:
- Generate summaries of each interaction from start to finish: Historical Summaries include all segments if multiple agents were involved.
- Convenient access for managers and analysts: Summaries are accessible within the Interaction Search interface of the Intelligence Engine application, as well as the Quality Management tools.
- On-Demand AI Summaries for any historical interactions: Even if Historical AI Summaries are disabled for a certain service, the option to "Generate Summary" is available in Interaction Search for any recorded interaction.
Summary Template
Despite their different applications, both Real Time and Historical summaries use a single Summary Template. Template characteristics:
- Template Structure: A template structures the summary by defining the section headers (e.g., "Reason for Contact," "Outcome"), and, for each header, an AI prompt to generate its content and a specification for the desired summary length.
- Hide From Agents Control: The visibility of individual headers to agents can be toggled within the template. This means specific information (e.g., "Agent Performance") can be included in the Historical AI Summary for manager and analyst review but hidden from the Real Time AI Summary / Notes that the agent sees.
- Template Assignment: A template assigned to a service is used to summarize all interactions for that service.
- Default Template: A system-default summary template is automatically used for any service with AI Summaries enabled if no other custom template has been assigned. This general-purpose template can be used as-is or customized.
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