
ISW AI
Convert Photos and speech into autocorrected word doc
What it does
ISW AI — Turn photos & voice into editable Word docs Most scanner apps still use old OCR — they hand you a wall of plain text with no structure. ISW AI is different: it uses AI vision that actually understands your content, so you get a real, editable Word document — with proper headings, bullet points, and tables. The image could be Snap a whiteboard, handwritten notes, or a printed page. With SpeechDictate or record right in the app → get a structured doc
Photograph a whiteboard, printed page, or handwriting — get back a clean, editable Word document. Real paragraphs, headings, and tables.
Photograph a whiteboard, a printed page, or your own handwriting. Get back a clean .docx you can actually edit — real paragraphs, real headings, real tables. Not a picture of your notes. The notes themselves, typed. Printed or handwritten, it becomes real editable paragraphs — not a scan. Titles and sections map to proper Word heading styles, so your document has structure. Grids become native Word tables you can edit cell by cell, not screenshots. Neat or rushed, your handwriting is read and typed out for you. Boxes and arrows rebuilt as editable Word shapes you can drag and relabel. Record a lecture or talk live — get a structured document, not just a transcript. Every account comes with…from isw-ai.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 · 16d 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 · 26d 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 · 16d ago · simedw.com