RecapSynth
Turn manga & manhwa chapters into video recaps in minutes
What it does
RecapSynth is an AI-powered desktop app that automates the repetitive workflow behind manga, manhwa, and Webtoon recap videos. Instead of spending hours cutting, arranging, scripting, and syncing assets, RecapSynth helps creators get from source material to an editable video project in minutes.
RecapSynth converts manga and manhwa chapters into automated YouTube recap timelines. Generate scripts, voiceovers and edit-ready projects in seconds. Built for recap creators.
Stop editing for hours. RecapSynth batch processes manga chapters into perfectly synced video timelines. Professional automated video production engineered to run locally on your GPU. Export universal .OTIOZ files for Premiere Pro, Resolve, or CapCut. Export.otioz Timeline Data AI Script TTS VOICE SYNC STATUS: BATCH PROCESSING Problem Identification The Old Way is Broken Creating recaps shouldn't feel like manual labor. Stop fighting with your timeline. Slicing pages, removing gutters, and stitching panels typically takes hours of repetitive clicking. Writing scripts from speech bubbles and syncing AI voice generation is an error-prone mess. Creators spend 20+ hours per video on repetitive…from recapsynth.com
Does the same job
all alternatives →
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io
- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com