Summary Generation
Data 360 extracts session summaries from your agent conversations through a real-time memory extraction pipeline. Summary generation processes conversations at regular intervals, capturing structured knowledge that persists across sessions and becomes immediately available for context retrieval in future conversations.
How Summary Generation Works
Data 360 extracts memories from conversation data periodically during the session. Extraction runs at intervals determined by message volume and elapsed time, balancing freshness with efficiency.
Each extraction cycle considers both new messages and previously extracted memories. This enables the pipeline to:
- Consolidate overlapping information across cycles.
- Remove duplicate memories.
- Resolve conflicts when newer information contradicts older information (recency wins).
- Build progressively richer and more accurate memories over time.
Extraction Triggers
| Trigger | Description |
|---|---|
| Size-based | Triggered when accumulated unprocessed messages reach approximately 50% of the LLM context window. This is the primary trigger during active conversations. |
| Time-based | Triggered after a configurable duration since the last extraction. Ensures memories are generated from low-volume conversations. |
| Session close | A final extraction cycle runs when a session is closed, processing any remaining unprocessed messages. |
What Gets Extracted
Each extraction cycle produces session summaries. These are compressed records of what happened in the conversation.
- Topics discussed and questions asked.
- Decisions made and outcomes reached.
- Actions taken by the agent and the user.
- Commitments and follow-up items.
- Key turning points in the conversation.
Session summaries give agents the ability to recall prior interactions without replaying full transcripts.
Considerations
- LLM processing: Memory extraction involves calling an LLM with the extraction prompt that generates structured output containing summaries. This consumes LLM usage credits.
- Memory storage: Data 360 stores all extracted memories as conversation memories.
- Language support: Memory extraction is language-agnostic. The LLM processes messages in whatever language the conversation uses and produces memories in that same language. You don’t need a separate translation step.
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