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Sageling

a local AI agent for Mac, Qwen 3.5 9B in-process via MLX

Details

External ID
49569136
Source
HN
Company
—
Product
Sageling
Website domain
sageling.ai
Launched
Sept. 4, 2026
Cohort
—
Upvotes
7
Upvotes percentile
0.4393939393939394
Tags
—
Fetched at
Sept. 10, 2026, 5:31 a.m.
Updated at
Sept. 10, 2026, 5:31 a.m.

Description

A lot of my non-developer friends still think that AI is basically just Google or something you ask to write something and then copy paste it around... if they use it at all. When I ask them why they don't use the good stuff like Claude Cowork or its competitors, they tell me a few things: 1. Well, I don't wanna pay a bunch of money for it, and the $20 plans run out real fast. 2. I'm dealing with sensitive info (student grades, therapy notes, legal work, etc) and I don't wanna give it to anyone.So I built Sageling to give them a first taste of what a good coworking experience feels like. It's admittedly not going to be as powerful given it's running Qwen 3.5 9B, but with all of the harness' tricks, it a good first experience that can handle some impressive things for its size (see all the website videos).If you've heard similar things from your friends, send the link onto them =)

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Agent / copilot
Audience
Prosumer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
local ai agent for mac
Manually corrected
False

Could you build this?

Partial Building a standard desktop UI is easy, but integrating Apple Silicon MLX C++/Swift bindings to run local 9B models and audio models in-process without memory crashes requires deep native systems optimization.

What it would actually take: Requires a native Swift/macOS app that directly interfaces with Apple MLX or llama.cpp via C/Obj-C bridges, alongside local Whisper models for speech-to-text. The hard part is memory budgeting to run a quantized 9B LLM and transcriptions simultaneously within 16GB of unified memory without UI stalls or thermal throttling, plus handling local tool-calling loops. Requires native Apple platform engineering and local machine learning inference expertise.

Discussion

1 comment analyzed.

Competitors

Other products that read as similar to this one — 161 launches clear the similarity bar, closest 8 shown.

Attention rank: #86 of 162 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 302 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a agent / copilot tool for Agriculture yet.