About Nokast

A studio for local-first AI

Nokast is an open-source AI studio and community. We build tools and share patterns โ€” privately, transparently, in public.

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What Nokast Is

A small AI studio, building in public

Nokast is a small AI studio building local-first tools and patterns: small language models, secure retrieval, and agentic workflows that run on your own machines. We share everything in public so other builders can copy, fork, and improve.

Our work includes LocalizeAI โ€” a privacy-first newsletter intelligence tool โ€” and Nodemind, a macOS cognition agent that builds a knowledge graph from your voice, extracts tasks, and schedules meetings.

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Why Local-First

Your data stays where it belongs โ€” with you

Most AI tools send your data to remote servers. We think that's the wrong default. Local-first AI means smaller attack surfaces, no vendor lock-in, and full ownership of your context.

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    Data stays on your devices

    No telemetry, no remote inference by default. Your notes, emails, and documents never leave your machine.

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    Small, efficient models

    SLMs (1Bโ€“7B parameters) run fast on consumer hardware โ€” MacBooks, gaming PCs, edge devices.

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    Transparent stacks

    No black-box APIs. Every component of the Nokast stack is open and inspectable.

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Community & Nokast Sessions

Nokast is more than a studio

Nokast is also a community of builders, researchers, and curious people joining the private GenAI wave together.

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    Nokast Sessions

    Small-group discussions to share ideas, demo experiments, and help each other build with local-first AI. Open to all skill levels.

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    Open contribution

    Issues and PRs welcome on GitHub. Join the conversation on Substack via comments and replies.

Who started this

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Abhishek

Member #0 ยท Founder

The first member of the Nokast open-source AI community. Started this to prove privacy-first, local AI is the right default โ€” and building it in public, one log at a time.

Connect with meabhishek.nokast.com

Get involved

Join a Nokast Session, follow the build log on Substack, or contribute on GitHub.