Summarising a long WhatsApp thread by hand, scrolling, copying, pasting, and prompting, is the slow path. The clean workflow is: export the chat, include voice messages if they matter, upload the `.zip`, and let a tool that understands WhatsApp do the structural work.
Turn this thread into meeting notes and action items.
Analyze your chatThis page walks through the full process end-to-end, including the parts most guides skip, voice message transcription, group chat filtering, credit math, and the privacy details that matter when you upload someone else's words to an AI tool.
The WhatsApp chat summariser is built around exactly this flow, upload an export, get structured analysis with action items, decisions, and timeline-aware voice transcription. To see how the approach differs from the alternatives, compare ThreadRecap with other WhatsApp chat analyzers.
If you already have a WhatsApp export `.zip`, you are one upload away from a clean recap.
The analysis returns a quick structured briefing:
After the briefing, the AI chat takes over: ask follow-up questions, pull exact quotes, and generate full documents (meeting minutes, task lists, timelines, evidence packets). Decisions and action items can be sent directly to Notion, Trello, or Google Calendar with one click.
On Samsung (One UI) the sheet has a Save as file entry, sometimes behind More, which writes the `.zip` to Downloads. On every other Android there is no such entry, so send it to Google Drive. When you upload later, the Android file picker lists Google Drive in its side menu, so you pick the `.zip` straight from there with no download.
Choose it if you have substantive content in voice messages, decisions, rationale, action items, anything spoken rather than typed. ThreadRecap transcribes the voice files and merges them into the timeline so the recap reflects the full conversation.
Choose "Without media" if the chat is mostly text and you want the smallest file. Without-media exports also have a higher message cap (40,000 vs 10,000 with media), which matters for long historical chats.
For a deeper trade-off discussion, see Summarise long WhatsApp chats.
The flow is:
There is nothing to configure up front. You shape the output after the briefing, in the AI chat that knows the whole conversation:
One-click actions appear for the detected conversation type, and paid documents arrive as polished downloadable files. When the chat is a recurring work sync, the meeting-minutes document lands directly as meeting minutes from a WhatsApp chat.
If the standard actions do not match your use case, type your own direction in the chat. It runs against the same parsed conversation, so date ranges and voice transcription still apply.
WhatsApp conversations often hide the substantive content in voice messages. A 3-minute voice message typically covers more ground than 50 text messages, especially in workflows where the people doing the substantive talking prefer to dictate.
ThreadRecap handles voice transcription as part of the same upload:
Without timeline merge, even a tool that "transcribes voice messages" will miss the substantive content because the analysis layer never sees the audio in conversation context. ThreadRecap's pipeline does the merge automatically.
For more on what to expect from voice transcription, see WhatsApp voice message accuracy. If transcription is the job rather than the summary, WhatsApp audio to text is the page for that.
Practical tip: if your chat relies on voice messages, export with media. Otherwise you are summarising only half the conversation.
ThreadRecap uses credits and charges per usage:
Plus modifiers:
Depth is priced separately, in the chat: the first five questions on each analysis are free and after that 1 credit buys four more, and generated documents (meeting minutes, evidence packets, full reports) start at 2 credits, rising with conversation size.
New users get 5 free credits on sign-up, which is enough to run a complete recap on a typical short or medium chat end-to-end before deciding whether to top up.
| Scenario | Credits |
|---|---|
| 800-message one-on-one chat, no voice messages | 1 |
| 3,500-message group chat, 20 min voice messages | 4 (messages) + 2 (audio) + 2 (group) = 8 |
| 10,000-message one-on-one chat, 60 min voice messages | 10 (messages) + 6 (audio) = 16 |
| 5,000-message group chat, no audio, plus one generated document | 5 + 2 (group) + 6 (document, over 2,000 messages) = 13 |
Depth happens in the chat, so one upload never pays for parsing or transcription twice.
Group chats explode token usage and signal-to-noise ratio. ThreadRecap's approach is to focus analysis on the participants whose contributions actually matter:
In a 12-person group chat, the three or four people doing 80% of the substantive talking are usually the ones your questions should target. Narrowing the date range also reduces credit cost.
Specific privacy claims:
For sensitive conversations (legal, medical, HR, family disputes), review the privacy policy before uploading. The retention specifics and deletion behaviour are detailed there.
WhatsApp's Advanced Chat Privacy feature can block export on a per-chat basis. The setting lives inside the individual chat, not at the device or account level. If export is blocked, someone in the chat enabled the restriction; you cannot bypass it from your side.
You exported without media. Re-export and choose Include media (Android) or Attach Media (iPhone).
Large media exports can be hundreds of megabytes or more. If you only need a text summary, export without media for a smaller file. If you need audio transcription, keep media but consider exporting a smaller date range, especially if the conversation spans years.
If the decision was made in a voice message and you exported without media, that decision is not in the chat log at all, the export shows "audio omitted". Re-export with media and re-run the analysis.
If the decision was in text but the briefing missed it, the cause is usually a date range that excluded it. Adjust the range and re-run, or simply ask the chat, which searches the full transcript.
That is exactly the case ThreadRecap is built for. See summarise long WhatsApp chats for the full multi-pass workflow at 5k, 10k, and 50k message scale.
Yes. The reliable approach is to export the chat as a `.zip` and run analysis on the export rather than scrolling and copying sections manually. A purpose-built tool handles the full chat in one pass and preserves coherence across thousands of messages.
Only if voice messages carry meaningful content. ThreadRecap supports `.opus` and `.m4a` audio and merges transcripts into the conversation timeline.
`_chat.txt` (the full message history) plus media files (`.jpg`, `.mp4`, `.opus`, `.m4a`, etc.) when media is included.
ThreadRecap parses `.zip` files locally in the browser, never uploads photos, videos, or documents, and stores chat text, voice message audio, and processed recaps encrypted in your account where you control deletion through the dashboard. Review the privacy policy before uploading sensitive conversations. If you select a video, your browser extracts and sends only its audio track for transcription. The video and its visual content stay on your device.
The UI is available in multiple languages and ThreadRecap can return outputs in the conversation's original language or in English. Voice transcription works across a wide range of languages.
Upload your WhatsApp export and run your first recap.
Upload your export and get decisions, action items, and a clean summary you can forward in minutes.
Summarize WhatsApp chat conversations instantly with AI—extract summaries, decisions, action items, and open questions from exported .zip files in minutes.
Upload your export and get decisions, action items, and a clean summary you can forward in minutes.