SecureMyReceipts
100% local AI receipt tracker. No cloud, no subscriptions.
What it does
Most of the existing tools out there either lock you into a monthly subscription or harvest your data behind the scenes. So, I decided to build a local-first alternative. 🔒 100% under YOUR control: Every function is local. All AI and OCR runs directly on your PC to read and organize your receipts. Your documents never go to the cloud. 💻 Real Windows App: Built usingNET MAUI with native Windows function calls. 💳 No Subscriptions!: You pay once, like in the good old days. No monthly fees.
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Agent Mode by Receiptor AIJun 2026 · receiptor.ai · ▲520Bookkeeping assistant that runs receipt workflows end-to-end
- IBI built a receipt processor for Paperless-ngxFeb 2026 · ▲6
Hi all, I wanted a robust way to keep track of my receipts without needing to keep them in a box and so i found paperless - but the existing paperless ai projects didn't really convert my receipts to usable data. so I created a fork of nutlope's receipthero (actually it's a complete rewrite, the only thing that remains over is the system prompt) The goal of this project is to be a one stop shop for automatically detecting tagged docs and converting them to json using schema definitions - that includes invoices, .... i can't think of any others right now, maybe you can? If you do please make…
- RGRAG-Guard: Zero-Trust Document AI2025 · github.com · ▲9
Hey HN, I wanted to share something I’ve been working on: *RAG-Guard*, a document AI that’s all about privacy. It’s an experiment in combining Retrieval-Augmented Generation (RAG) with AI-powered question answering, but with a twist — your data stays yours. Here’s the idea: you can upload contracts, research papers, personal notes, or any other documents, and RAG-Guard processes everything locally in your browser. Nothing leaves your device unless you explicitly approve it. ### How It Works - * Zero-Trust by Design*: Every step happens in your browser until you say otherwise. - * Local…
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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.
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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, June 2026
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Today, I’m proud to announce Homebrew 6.0.0. The most significant changes since 5.1.0 are a new tap trust security mechanism, the new faster, smaller, default internal Homebrew JSON API, sandboxing on Linux, better defaults informed by our user survey, many brew bundle improvements, improved performance and initial support for macOS 27 (Golden Gate). Happy to discuss any questions here!
Dev tools · Jun 2026 · brew.sh
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Life & fun · Jun 2026 · vorpus.github.io
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