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MacPaw is building an on-device AI layer that will work across your Mac apps

MacPaw announced a long-term strategic partnership with Liquid AI to co-develop an on-device AI technology stack for macOS, starting with its Eney AI assistant. The collaboration will adapt Liquid AI's Liquid Foundation Models for Mac-based assistance and combine them with MacPaw's Mnemos memory and Elix inference technologies, with plans to extend the stack to more MacPaw products and make it available to Mac developers through Setapp.

read1 min views1 publishedAug 5, 2026
MacPaw is building an on-device AI layer that will work across your Mac apps
Image: 9To5Mac (auto-discovered)

MacPaw has announced a long-term strategic partnership with Liquid AI to co-develop an on-device AI technology stack built specifically for the Mac.

The collaboration will start with Eney, MacPaw’s AI assistant for macOS.

MacPaw is teaming up with Liquid AI to bring more on-device AI to the Mac #

Liquid AI’s Liquid Foundation Models (LFMs) will be adapted for Mac-based assistance and combined with MacPaw’s own on-device technologies: Mnemos for memory and Elix for inference.

Eney already shifted to a local model last year, keeping reasoning, contextual search, skill execution, and conversation history on the device whenever possible.

The new partnership is intended to push that approach further. The two companies are jointly developing the underlying stack rather than MacPaw simply adding another third-party model.

Once the technology has been tested and implemented in Eney, MacPaw says it plans to bring it to more of its products. It also wants to make the shared AI stack available to Mac developers through Setapp.

That could let participating apps expose more of their capabilities and context to Eney. This would allow the assistant to understand what is inside an app. It could also provide more useful answers or take relevant actions.

You can learn more about MacPaw’s on-device AI technology and today’s announcement here, and catch up on Liquid AI here.

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