Group Chat Recap by Participant
Filter group chat analysis to specific participants and get a focused recap instead of a noisy summary of everyone.
A group chat with 20 people is noisy. You do not care what everyone said — you care what specific people said. Maybe the project lead, the client, or the two engineers working on the critical feature.
Participant filtering turns a chaotic group recap into a focused summary.
The noise problem in group chats
In a typical work group chat:
- 3-5 people drive the important discussions
- 5-10 people contribute occasionally
- The rest react, share memes, or have side conversations
When you summarize the entire chat, the noise dilutes the signal. Action items from the project lead get mixed with lunch plans and emoji reactions.
How participant filtering works
When you upload a WhatsApp export to the group chat summarizer, the system detects all participants in the chat. Before running the analysis, you select which participants to focus on.
Messages from unselected participants are treated as background context — they are visible to the AI but not the focus of the analysis.
This means:
- The summary centers on what your selected participants said
- Action items are extracted primarily from their messages
- Decisions reflect their discussions and agreements
- Voice notes from selected participants are transcribed and prioritized
Use cases for participant filtering
Project lead + key engineers
In a 15-person project group, filter to the project lead and the 2-3 engineers on the critical path. The recap shows what they decided, what they committed to, and what they need.
Client-facing summary
Filter to only client-facing team members. The recap captures what was communicated to or about the client, making it easy to write a client update.