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ThreadRecap
ThreadRecap turns WhatsApp exports into structured, timestamped reports you can act on or hand to someone else.
What it does
Who it is for
Solo professionals in real estate, HR, recruiting, law and client services who need a defensible record of what was agreed, plus anyone catching up on long work, family or community threads.
How it works
Export the chat from WhatsApp, upload the .zip or .txt, choose an analysis goal, get the report in seconds. No setup, no integration, no account for the other participants.
Pricing
Credit packs with no subscription required, plus an optional monthly plan for regular use. Free credits on signup.
Languages
English, Portuguese, Spanish, German, Italian and French.
Independent and bootstrapped, launched in January 2026.
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ThreadRecap's answer:
Most summarizers expect you to paste text. ThreadRecap takes the raw WhatsApp export, the .zip with thousands of messages and voice notes, and turns it into a timestamped record you can hand to someone else. Voice messages are transcribed and merged into the same timeline as the text, so a commitment made in a 4 minute audio at 11pm sits in date order next to everything else. The output is not a paragraph of prose. It is decisions, agreements, deadlines, responsibilities and quoted messages, in chronological order.
ThreadRecap's answer:
Generic AI assistants can summarize a chat you paste, but they hit token limits on long threads, ignore voice notes, and give you a different structure every time you ask. Chat statistics tools give you word clouds and message counts, which is not what you need when you are trying to prove what was agreed. ThreadRecap is built for the specific job of turning a full export into a structured, repeatable record. It works in six languages, needs no integration or account for the other participants, and you pay per analysis instead of subscribing.
ThreadRecap's answer:
Solo professionals and individuals who need to establish what was actually agreed in a conversation. In practice: real estate agents, recruiters and HR, small business owners, freelancers dealing with clients, and people documenting a personal dispute over a rental, a partnership or a family matter. A second, lighter audience uses it to catch up on long work or family group chats. Buyers are spread across more than 20 countries, led by the UK, the US, Italy and Switzerland.
ThreadRecap's answer:
It started as a personal tool. I kept receiving long voice notes and endless work threads, and wanted the main points without listening to everything again. I built the first version over a weekend and published it as a proof of concept, mostly to see whether anyone else cared. People did, but not for the reason I expected. Instead of catching up on chats, they were using it to document disputes, prove agreements and produce a record of what was said. That reframed the whole product, and the roadmap has followed the users ever since.
ThreadRecap's answer:
Next.js and React with TypeScript, Tailwind CSS, Node.js on the backend, deployed on Vercel. Voice note transcription uses OpenAI Whisper, analysis runs on large language models, and payments go through Stripe.
Based on our record, umami seems to be more popular. It has been mentiond 97 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I self-host Umami for my SaaS, ParserBee. The main reason I picked it: privacy-friendly, cookie-less, first-party analytics that adblockers supposedly leave alone because the script comes from your own domain. - Source: dev.to / about 2 months ago
Umami told me Clew Directive got 14 visits last month. AWS told me I owed $31 for it. That works out to $2.21 a visitor, which would make it the most expensive free learning-path tool in California. - Source: dev.to / 2 months ago
Also a small tooling aside — if you're tracking how often skills get used across your team (or just want analytics on your dev blog without the GDPR cookie banner dance), privacy-focused options like Umami or Plausible give you full data ownership and a much lighter footprint than Google Analytics. I migrated two side projects to Umami last year and haven't looked back. - Source: dev.to / 4 months ago
Augur targets EU-regulated buyers. Putting Google Analytics on its landing page would be a self-own. I run Umami inside Augur's stack — same Docker Compose, same Postgres pattern, same backup discipline — privacy-clean, cookie-banner-free, GDPR-easy. The analytics endpoint is internal to the stack; nothing leaves the box. - Source: dev.to / 4 months ago
So this post is about something I've been chewing on for months but finally moved on: ripping Google Analytics out of three side projects and picking a privacy-focused alternative. Specifically, I'll compare Umami, Plausible, and Fathom — the three I actually evaluated — and walk through the migration steps that worked for me. - Source: dev.to / 4 months ago
Plausible.io - Plausible Analytics is a simple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics. Made and hosted in the EU, powered by European-owned cloud infrastructure 🇪🇺
Fathom Analytics - Simple, trustworthy website analytics (finally)
Matomo - Matomo is an open-source web analytics platform
Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.
Simple Analytics - The privacy-first Google Analytics alternative located in Europe.
Mixpanel - Mixpanel is the most advanced analytics platform in the world for mobile & web.
