
Apify
import.io
Octoparse
Bright Data
ParseHub
Zyte
ScrapingBee
Scrapy
ThreadRecap
Apify is a JavaScript & Node.js based data extraction tool for websites that crawls lists of URLs and automates workflows on the web. With Apify you can manage and automatically scale a pool of headless Chrome / Puppeteer instances, maintain queues of URLs to crawl, store crawling results locally or in the cloud, rotate proxies and much more.
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.
Apify
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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, Apify seems to be more popular. It has been mentiond 48 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.
The first network smoke labeled https://apify.com/ inconclusive even though the page was healthy. The response carried a Content Security Policy header larger than aiohttp's default 8 KB field limit. The client failed while parsing headers, before I saw the 200. - Source: dev.to / 4 days ago
Native @apify scheduling, dataset exports (CSV/JSON), webhooks, and it's callable by AI agents via Apify MCP. - Source: dev.to / 16 days ago
That runs News Scraper on Apify, which is the same forty lines plus the parts that are Tedious rather than hard: both feeds, the nested publisher element, the date Normalisation, and deduplication. - Source: dev.to / about 1 month ago
That runs an Apify Actor I maintain, Domain Scraper, because the Tedious parts are the RDAP bootstrap, the vcard unpacking and the provider Fingerprinting rather than the HTTP call. If you would rather do it yourself, Https://rdap.org/domain/ is the whole API and it needs no key. - Source: dev.to / about 1 month ago
Data collection: Apify actors, one per source, that scrape the open-data endpoints and normalize them. Quebec RBQ ships a daily bulk CSV (inside a 10.8 MB zip, ~924k rows that dedupe to ~54k active licences). Ontario HCRA has no bulk file — it's an internal JSON API behind the public registry. - Source: dev.to / about 2 months ago
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