Glicol
Sonic Pi
Strudel
SuperCollider
Overtone
Web Audio Studio
Faust
Klangmeister
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.
ThreadRecapThreadRecap'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, Glicol seems to be more popular. It has been mentiond 45 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.
Congratulations on your release, Sam! Are you still considering hardware demos, such as those on Raspberry Pi? If anyone here also wants to try a different syntax, check out http://glicol.org/. - Source: Hacker News / 30 days ago
Note: Nick Collins and Alex McLean created Algorave. The time I spent learning from the Algorave community was crucial to my later work on Glicol (https://glicol.org/). Btw, I have a feeling that if you want to learn about computer music, you can send the PDF to LLM and ask what the chapter is about and how to represent it using csound or supercollider. My experience is that with computer music, you have to keep... - Source: Hacker News / 5 months ago
I'm rewriting glicol (https://glicol.org/) with no std, and embassy-rs + 2350 is my go-to choice. Highly recommand this stack if you're planning to start working with embedded systems in 2026. - Source: Hacker News / 8 months ago
Relevant to this discussion - my project Glicol (https://glicol.org) addresses this space. Currently working on a no_std rewrite, demo coming next year :). - Source: Hacker News / 9 months ago
Some simple thoughts: I feel that one challenge of programming languages is how to remember these rules, formats, and keywords. Even if you're using familiar formats like YAML or JSON, how do you match keywords? When developing Glicol (http://glicol.org/), I found that if it's based on an audio graph, all node inputs and outputs are all signals, which at least reduces the matching problems. The remaining... - Source: Hacker News / 9 months ago
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