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Hacker News Show HN: Hitoku Draft – context aware local macOS assistant

A privacy-focused, local-first AI assistant for macOS that understands screen context, documents, and active applications to perform tasks like querying PDFs, replying to emails, and creating calendar events via voice.

4
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0
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Apr 14, 2026
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Product Positioning & Context

AI Executive Synthesis
A privacy-focused, local-first AI assistant for macOS that understands screen context, documents, and active applications to perform tasks like querying PDFs, replying to emails, and creating calendar events via voice.
The market for local-first AI solutions is expanding, driven by privacy concerns and the desire for offline functionality. Hitoku Draft directly addresses this by offering a context-aware, voice-first AI assistant for macOS that operates entirely on-device. Its ability to interpret screen content and active applications provides a significant productivity advantage, enabling seamless integration into daily workflows. Supporting multiple LLMs and STT backends offers flexibility, though performance and resource consumption challenges with Gemma 4 highlight the ongoing optimization required for local model deployment. This product targets power users and privacy-conscious professionals, positioning itself against cloud-dependent alternatives. The open-source nature could accelerate feature development and community adoption, establishing a strong foothold in the niche of secure, on-device AI assistance.
I am working on Hitoku Draft. An open-source, voice-first AI assistant that runs entirely locally. No cloud models, nothing leaves your machine. You press a hotkey, and you talk.It's context-aware; it reads your screen, documents, and active app to understand what you're working on. You can ask about PDFs, reply to emails, create calendar events, use web search, all by voice.It supports Gemma 4 and Qwen 3.5 for text generation, plus multiple STT backends (Parakeet, Whisper, Qwen3-ASR).Examples:- Gemma4 in action, https://www.youtube.com/watch?v=OgfI-3YjEVU- query a pdf document, https://www.youtube.com/watch?v=ggaDhut7FnU- reply to email, https://www.youtube.com/watch?v=QFnHXMBp1gA- and the usual voice dictation (with optional polishing)I currently use it a lot with Claude Code, Obsidian and Apple Notes, or just read papers.Code: https://github.com/Saladino93/hitokudraft/tree/litertDownload of binary: https://hitoku.me/draft/ (free with code HITOKUHN2026)I am looking for feedback. My goal is to do AI research with clients interfacing, and I thought this is a nice little experiment I could do to iterate/fail quickly.P.S. (if anyone has tips about this)Current Gemma4 implementation (with small models) has some problems:- easy to hallucinate for long contexts, so had to reset it often. Tuned some parameters, but need to find a sweet spot.- Gemma4 with LiteRT is currently fast compared to the MLX implementation of Qwen3.5 (like 3x faster on my machine when dealing with images). But it has the price of memory spikes. I believe this is because LiteRT's WebGPU backend can allocate significantly more GPU memory than the model weights alone (I got 38GB of memory taken, for the E4B~4GB model!). I guess we need to wait for Google for this.- App size: because no official Swift package from Google yet, have to bundle some file (LiteRT dylibs) that adds ~98 MB to a previous MLX only version (total app goes from ~50 MB to ~150 MB)If any of this bothers you: use Qwen 3.5 instead (pure MLX), or wait for the upstream fixes from Google :)Otherwise, for the mid-term I plan to switch to a potentially slower, but safer, MLX version for Gemma4 (hopefully on the weekend).
Open-source voice-first AI assistant runs entirely locally no cloud models context-aware reads screen documents active app

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What is Hitoku Draft – context aware local macOS assistant?
Hitoku Draft – context aware local macOS assistant is analyzed by our AI as: A privacy-focused, local-first AI assistant for macOS that understands screen context, documents, and active applications to perform tasks like querying PDFs, replying to emails, and creating calendar events via voice.. It focuses on The market for local-first AI solutions is expanding, driven by privacy concerns and the desire for offline functionality. Hitoku Draft directly ad...
Where did Hitoku Draft – context aware local macOS assistant originate?
Data for Hitoku Draft – context aware local macOS assistant was aggregated directly from the Hacker News community ecosystem, representing raw developer and early-adopter sentiment.
When was Hitoku Draft – context aware local macOS assistant publicly launched?
The initial public indexing or launch date for Hitoku Draft – context aware local macOS assistant within our tracked developer communities was recorded on April 14, 2026.
How popular is Hitoku Draft – context aware local macOS assistant?
Hitoku Draft – context aware local macOS assistant has achieved measurable traction, logging over 4 traction score and facilitating 0 recorded discussions or engagements.
Which technical categories define Hitoku Draft – context aware local macOS assistant?
Based on metadata extraction, Hitoku Draft – context aware local macOS assistant is categorized under topics such as: Open-source, voice-first AI assistant, runs entirely locally, no cloud models.
What are some commercial alternatives to Hitoku Draft – context aware local macOS assistant?
Our semantic intelligence engine identifies potential commercial alternatives in the SaaS space, such as PopTask, which offers overlapping value propositions.
How does the creator describe Hitoku Draft – context aware local macOS assistant?
The original author or development team describes the product as follows: "I am working on Hitoku Draft. An open-source, voice-first AI assistant that runs entirely locally. No cloud models, nothing leaves your machine. You press a hotkey, and you talk.It's context-aware;..."

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