Loadster
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ThreadRecap
Loadster is a cloud-based load testing and synthetic monitoring platform for engineers who want to know how their applications behave under real traffic.
Tests run with three types of bots: Protocol Bots for HTTP testing, headless Browser Bots that render full pages and execute JavaScript in real Chrome browsers, and Playwright bots for when you want to use Playwright JS directly.
Loadster scripts can be recorded from Chrome or Firefox with the Loadster Recorder extension, edited in a built-in editor with variables, datasets, and shared includes, and then replayed from multiple cloud regions.
Each test run returns detailed page timings (TTFB, FCP, LCP, CLS, etc) alongside resource waterfalls, screenshots, and full traces you can step through in a self-hosted trace viewer. Tests scale from a handful of virtual users (bots) to hundreds of thousands across distributed cloud engines without you provisioning anything.
The same scripts can be set up as monitors that run on a schedule from chosen regions. Notification policies route incidents to email, SMS, voice, or integrations like Slack and PagerDuty. Projects, roles, and shared test history keep teams aligned on what passed, what failed, and what changed.
Pricing is usage-based via Loadster Fuel, with 50 free units on sign-up and no credit card to start.
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.
Loadster ThreadRecapNo ThreadRecap videos yet. You could help us improve this page by suggesting one.
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.
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