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Products that do what Omni – Local-first multimodal file search on macOS does

Finally made something I've always wanted, using the model we built. • SOTA omni embedding model, fully local, indexes text, PDF, image, audio, and video • Swift-native app UI + mlx-swift-transformer core. No Python. • Tested on M3 Pro 18G / M3 Ultra 512G / M4 Pro 48G. All work fine. • HTTP server exposes search to local agents like OpenClaw & Hermes − Indexing still feels slow even on the latest M3 Ultra, ranging from 10K tps to 300 tps depending on file type − Fans go crazy, high power draw while indexing − Search is near-instant. Multimodal relevance is sometimes arguable, but…

  1. 1

    The end-to-end model powering multimodal chat

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  2. 2

    A native omni model for voice, video, and tools

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  3. 3

    Native end-to-end multilingual omni-modal LLM

    Sep 2025

  4. 4
    Fenn147

    Find what you need on your Mac. Even inside frames

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  5. 5
    Omnipilot242

    Autocomplete and in-context generation everywhere on macOS

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    Effortless image to text conversion for Mac

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  7. 7
    Omni97

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    Omni234

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  9. 9

    A native macOS client for Hacker News, built with SwiftUI

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  10. 10
    Mirowl96

    Search all your screenshots via a local OCR-powered AI

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  11. 11
    NoteTabs129

    Native macOS text editor with horizontal tabs & auto-restore

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    Zush87

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  13. 13
    AVE72

    Local-first AI video editor for Mac

    Jul 2026 · aivideoeditor.app

  14. 14OC

    I built an open source version of OpenAI Chronicle. Some design decisions I made: 1. Local first: OCR uses Apple Vision, summarization supports local AI providers via Vercel AI SDK. Nothing leaves your computer. 2. Multiple Provider: exposes MCP so any coding agents can use it. 3. Swift menubar app: efficient, low-footprint 4. Blacklist apps: password managers, messaging apps (Slack, WhatsApp, Messenger), mail clients are on default blocklist. Current Limitations: 1. Mac only. Mac-first is a feature. 2. Small local models with weak structured-output support will fail on generateObject. 3.…

    Apr 2026 · github.com

  15. 15OS
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  17. 17OS

    Introducing Nia Vault, a CLI that lets you query your local markdown/text files using natural language. What it does: Semantic search over local folders and notes Works across multiple synced directories RAG-style answers with citations from your own files How it works: Calls `POST /search/query` with `local_folders` Uses `search_mode: sources` to return answers + file references Example: vault ask "What are my notes about project planning?" OSS: https://github.com/chenxin-yan/nia-vault

    Feb 2026 · github.com

  18. 18JN

    My startup's just released this open source tool which lets you perform multimodal search in two lines. I would love to hear what you all think about it, or if you have any use case ideas in mind. It even helps Emojipedia improve its results. read the blog here: https://medium.com/jina-ai/jina-now-the-one-liner-neural-sea...

    2022 · now.jina.ai

  19. 19IM

    Hello all, I made a small transcription app for your Mac based on OpenAI’s Whisper. Would love some feedback. My plan is to make it easy to load weights from any fine-tuned whisper model to enable specialized dictation for any subfield. It’s still early in development. Thanks!

    2023 · twitter.com

  20. 20IB

    After getting frustrated with macOS's Spotlight search, e.g., typing "driver license" doesn't give me anything unless the file name matches exactly, I thought, why not index my entire Documents folder? This way, I can find that one PDF or image buried deep in subfolders using natural language queries. So I built SmartSearch; it uses SentenceTransformers for embeddings and FAISS for fast similarity search. Best of all, it runs locally on your computer. Github: https://github.com/neberej/smart-search/ Demo:…

    2025 · github.com

  21. 21AT

    I’ve been working on AnyModal, a framework for integrating different data types (like images and audio) with LLMs. Existing tools felt too limited or task-specific, so I wanted something more flexible. AnyModal makes it easy to combine modalities with minimal setup—whether it’s LaTeX OCR, image captioning, or chest X-ray interpretation. You can plug in models like ViT for image inputs, project them into a token space for your LLM, and handle tasks like visual question answering or audio captioning. It’s still a work in progress, so feedback or contributions would be great. GitHub:…

    2024 · github.com

  22. 22UA

    Most of the document parsers fail on real world challenges like complex tables, handwritten documents, historical document scans, equations, multi-column layouts, complex reading order, etc. We built Unsiloed Parser to handle exactly these cases. Our latest parser v3.1 achieved #1 rank and scored 88.0 strict pass-rate on olmOCR-Bench. We ran the evaluation across 1,403 PDFs and 8,413 unit tests using the unmodified upstream Allen AI scorer (olmocr==0.4.27) and found Unsiloed beats 18 other OCR services, including GPT-5.5, Claude Opus 4.7, LlamaParse, Reducto, Azure Document Intelligence, AWS…

    May 2026

  23. 23IM

    Textpod is a simple UI on top of a single notes.md file + a few features I always wanted: - add + in front of a link to fetch a local copy of the page (downloaded in the background using monolith[1]) - search is integrated into the note input, just start typing with / - attach images and other files (stored in 'attachments' directory) I made a 1-minute demo video (no sound) [2]. When you start the binary, the data is served from the current directory: the notes file and the attachments directory are created automatically. Run multiple instances from different directories, if needed (I…

    2024 · github.com

  24. 24VA

    Dear HN Community, I am a long time fan and first-time contributor. I just launched a developer focused semantic search platform and wanted to share it with the community. The idea is simple: upload structured or unstructured documents, select the fields you want to index and tag as metadata, and instantly get a clean search API you can use in your own app. Here is what it currently supports: - Manage your own tenants and projects - Upload .json and .txt files (support for .pdf, .docx, .xlsx, .yml, etc. coming soon) - Expose 3 APIs: search, upload document (embeddings), and delete document -…

    2025 · aisearch.vpuna.com

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