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The missing orchestration layer

AI models are powerful, but they're stuck in silos. A vision model in one app. An LLM in another. A transcription tool somewhere else. They don't talk to each other.

MachineFabric connects them. Drop a file, watch it flow through extractors, vision models, LLMs—whatever chain makes sense. The models don't know about each other. MachineFabric handles the wiring.

AI models as Unix commands

Unix solved this fifty years ago: small tools that do one thing, connected by pipes. The output of one becomes the input of the next.

MachineFabric treats AI models the same way. Each model is a black-box command. A vision model takes an image, outputs a description. An LLM takes text, outputs text. MachineFabric chains them together.

Example: Processing a PDF
Input
research-paper.pdf
→ Extract
Text and images from each page
→ Vision
Describe figures and diagrams
→ LLM
Summarize, translate, analyze
Capability URNs
Extract
cap:in="media:application/pdf";op=extract
Describe
cap:in="media:image/png";op=describe
Translate
cap:in="media:text/plain";op=translate;lang=fr

Loose coupling, real interoperability

Plugins advertise what they can do using capability URNs. What inputs they accept, what outputs they produce. MachineFabric matches capabilities to find chains automatically.

The protocol is minimal: stdin/stdout with CBOR frames. Any language that can read and write bytes can be a plugin. The community writes plugins without coordinating with us.

Local AI, no API keys

MachineFabric runs AI models on your Mac using MLX and Metal. Vision models, LLMs, transcription—all local.

No API keys. No usage limits. No sending your files to a server. Download a model once, run it forever. Works offline.

Local Models
Vision
Image and document understanding
LLM
Analysis, summarization, translation
MLX
Apple Silicon optimized inference
Bundled Plugins
pdfcartridge txtcartridge mlxcartridge ggufcartridge
Community Plugins
Audio transcription coming
Video processing coming
Your model here write it

Community plugins

Plugins are standalone binaries. Any language that can read stdin and write stdout works. We have reference implementations in Rust, Swift, Go, and Python.

Someone wraps a new open-source model? Package it as a plugin. A better PDF extractor drops? Wrap it. The ecosystem grows without bottlenecks.

Native macOS, not Electron

MachineFabric is a native Mac app. SwiftUI, AppKit, Metal for GPU acceleration. It feels like part of the system because it is.

Drag files from Finder. Results appear in a native window. No web views, no embedded browsers, no "this page is unresponsive" dialogs.

Your files stay on your Mac

No cloud uploads. No "processing on our servers." AI models run locally. Everything is stored locally. Unplug your internet—MachineFabric keeps working.

Local AI
Local storage
Works offline

What's shipping

We're launching with plugins for PDFs, EPUBs, images, and text files. Vision models for image understanding. LLMs for text processing.

Working now: PDF extraction, image description, MLX inference, the plugin protocol, native macOS UI.

Coming: More models, more file types, audio transcription, video processing—whatever the community builds.

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