SaaS Metrics
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 the idea is recall (the agentic LLM takes the results and refines for the final answer), so maybe that's fine
Show HN: Omni – Local-first multimodal file search on macOS
Local-first multimodal file search on macOS using a SOTA omni embedding model, indexing text, PDF, image, audio, and video.
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AI Executive Synthesis
Local-first multimodal file search on macOS using a SOTA omni embedding model, indexing text, PDF, image, audio, and video.
Omni targets the critical need for efficient, private, and comprehensive local data retrieval on macOS. Its 'local-first multimodal' approach, indexing diverse file types with a SOTA embedding model, represents a significant advancement over traditional search. The 'Swift-native app UI + mlx-swift-transformer core' emphasizes performance and platform integration, avoiding Python dependencies. While indexing speed and power consumption are noted challenges, the 'near-instant' search and 'recall' focus for agentic LLMs highlight its strategic value. This product addresses the growing demand for personal AI agents that can access and synthesize local information without cloud dependency, enhancing privacy and reducing latency. It positions itself as a foundational component for future local AI workflows, enabling richer context for agents like OpenClaw and Hermes.
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Deep-Dive FAQs
What is Omni – Local-first multimodal file search on macOS?
Omni – Local-first multimodal file search on macOS is analyzed by our AI as: Local-first multimodal file search on macOS using a SOTA omni embedding model, indexing text, PDF, image, audio, and video.. It focuses on Omni targets the critical need for efficient, private, and comprehensive local data retrieval on macOS. Its 'local-first multimodal' approach, inde...
Where did Omni – Local-first multimodal file search on macOS originate?
Data for Omni – Local-first multimodal file search on macOS was aggregated directly from the Hacker News community ecosystem, representing raw developer and early-adopter sentiment.
When was Omni – Local-first multimodal file search on macOS publicly launched?
The initial public indexing or launch date for Omni – Local-first multimodal file search on macOS within our tracked developer communities was recorded on June 6, 2026.
How popular is Omni – Local-first multimodal file search on macOS?
Omni – Local-first multimodal file search on macOS has achieved measurable traction, logging over 5 traction score and facilitating 1 recorded discussions or engagements.
Which technical categories define Omni – Local-first multimodal file search on macOS?
Based on metadata extraction, Omni – Local-first multimodal file search on macOS is categorized under topics such as: Local-first, multimodal file search, macOS, SOTA omni embedding model.
What are some commercial alternatives to Omni – Local-first multimodal file search on macOS?
Our semantic intelligence engine identifies potential commercial alternatives in the SaaS space, such as Qwen3.5-Omni, which offers overlapping value propositions.
Are there open-source alternatives related to Omni – Local-first multimodal file search on macOS?
Yes, the GitHub ecosystem contains correlated projects. For example, a repository named fikrikarim/parlor shares highly similar architectural descriptions and topics.
How does the creator describe Omni – Local-first multimodal file search on macOS?
The original author or development team describes the product as follows: "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-transforme..."
Community Voice & Feedback
No active discussions extracted yet.
Discovery Source
Hacker News Aggregated via automated community intelligence tracking.
Tech Stack Dependencies
No direct open-source NPM package mentions detected in the product documentation.
Media Tractions & Mentions
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Deep Research & Science
No direct peer-reviewed scientific literature matched with this product's architecture.