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  # SmartTasks
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  **Local-first desktop automation, powered by governance-validated AI.**
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- SmartTasks builds tools that keep humans in command of their workflows β€” and of the
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- AI those workflows increasingly rely on. Two things live here, tied together by the
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- models we publish on this page.
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  ---
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  ## πŸ–₯️ SmartTasks β€” Desktop Automation Platform
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- A no-code, **local-first** automation platform. Build powerful workflows with a
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- visual drag-and-drop builder, connect any desktop app, and run everything natively
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- on your own machine β€” full data privacy, no cloud upload required for execution.
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  - **Visual drag-and-drop builder** β€” triggers, actions, conditions, loops, sub-flows. No code.
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  - **14 core plugins + Marketplace** β€” AI Tools, Data Storage, Scheduler, HTTP, Email, Webhook, and more.
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  ## πŸ›‘οΈ IAIso β€” The Governance Framework
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- As automation platforms hand more decisions to autonomous AI, **IAIso** provides the
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- mechanical constraints that keep humans in command: hard-coded **system invariants**
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- AI cannot cross, and **human override** built into the decision circuit. It's the
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- governance layer behind everything we ship.
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  β†’ [IAIso.org](https://iaiso.org) Β· [github.com/SmartTasksOrg/IAISO](https://github.com/SmartTasksOrg/IAISO)
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  ## πŸ€– The Models on This Page
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- The GGUF models we publish here are the bridge between the two: **local AI, validated
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- against IAIso invariants**, ready to power SmartTasks automation privately and
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- on-device. Unlike a bare quantized re-upload, each ships with a documented,
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- machine-readable governance profile so you can decide whether a model is fit for an
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- autonomous loop *before* you wire it in:
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  - **Capability scorecard** β€” instruction-following, reasoning, structured output, and tool-calling, mapped to a capability tier (`scorecard.json`, machine-readable).
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  - **Red-team security assessment** β€” resistance to prompt-injection and jailbreak probes, reported honestly per attack class (weak spots included, not hidden).
 
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+ ---
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+ title: README
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+ emoji: πŸ“‰
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+ colorFrom: purple
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+ colorTo: blue
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+ sdk: static
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+ pinned: false
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+ ---
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+
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  # SmartTasks
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  **Local-first desktop automation, powered by governance-validated AI.**
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+ SmartTasks builds tools that keep humans in command of their workflows β€” and of the AI those workflows increasingly rely on. Two things live here, tied together by the models we publish on this page.
 
 
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  ---
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  ## πŸ–₯️ SmartTasks β€” Desktop Automation Platform
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+ A no-code, **local-first** automation platform. Build powerful workflows with a visual drag-and-drop builder, connect any desktop app, and run everything natively on your own machine β€” full data privacy, no cloud upload required for execution.
 
 
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  - **Visual drag-and-drop builder** β€” triggers, actions, conditions, loops, sub-flows. No code.
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  - **14 core plugins + Marketplace** β€” AI Tools, Data Storage, Scheduler, HTTP, Email, Webhook, and more.
 
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  ## πŸ›‘οΈ IAIso β€” The Governance Framework
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+ As automation platforms hand more decisions to autonomous AI, **IAIso** provides the mechanical constraints that keep humans in command: hard-coded **system invariants** AI cannot cross, and **human override** built into the decision circuit. It's the governance layer behind everything we ship.
 
 
 
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  β†’ [IAIso.org](https://iaiso.org) Β· [github.com/SmartTasksOrg/IAISO](https://github.com/SmartTasksOrg/IAISO)
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  ## πŸ€– The Models on This Page
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+ The GGUF models we publish here are the bridge between the two: **local AI, validated against IAIso invariants**, ready to power SmartTasks automation privately and on-device. Unlike a bare quantized re-upload, each ships with a documented, machine-readable governance profile so you can decide whether a model is fit for an autonomous loop *before* you wire it in:
 
 
 
 
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  - **Capability scorecard** β€” instruction-following, reasoning, structured output, and tool-calling, mapped to a capability tier (`scorecard.json`, machine-readable).
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  - **Red-team security assessment** β€” resistance to prompt-injection and jailbreak probes, reported honestly per attack class (weak spots included, not hidden).