qRaptor - Turn business intent into production AI apps
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qRaptor is the AI-Native Application Engineering & Execution Platform. Build production-ready apps and AI agents on one platform ā humans and AI agents working as one, governed by design. Deploy anywhere, own your code.
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Maker
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Hey Product Hunt š
We built qRaptor because we kept seeing the same gap: AI demos are everywhere, but almost none of them survive contact with a real business. Production means accountability, access control, and humans in the loop ā not just a clever model.
qRaptor is an AI-native application engineering & execution platform. You describe what you need, and it turns that intent into a real, deployable system:
š§± Build full-stack apps ā from a prompt to a complete app (built on an app context graph), deployable in one click
š¤ Appoint AI agents ā give them skills & tools, deploy as a copilot or API, run autonomously on any event or schedule
āļø Automate task agents ā design with drag & drop, validate against real scenarios, deploy as scheduled or event-driven APIs
š”ļø Governance built in ā RBAC, human-in-the-loop, and full audit & observability, so nothing runs in the dark
Apps, data, agents, and automation ā one unified system.
We'd love your honest feedback, and we're around all day to answer anything.
š Try it: https://studio.qraptor.ai
š Learn more: https://qraptor.ai
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Honestly the agent handoff feels smoother than I expected, like it actually knows when to step back instead of just yapping through everything. Curious how it holds up on messier internal workflows.
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Maker
@creatorproĀ the agent handoff is complete depending on the usecase, Example : For the app generation we have multi agent system, wherein there is a combination of ReAct + Deterministic algorithmic methods are used to decided if the loop continues without stopping.. For internal workflows we have two things, ReAct agent ( AI Agent in qRaptor ) + Deterministic Flows ( Task Agent ) wherein we dont need reasoning loops..
Replies
Honestly the agent handoff feels smoother than I expected, like it actually knows when to step back instead of just yapping through everything. Curious how it holds up on messier internal workflows.
@creatorproĀ the agent handoff is complete depending on the usecase, Example : For the app generation we have multi agent system, wherein there is a combination of ReAct + Deterministic algorithmic methods are used to decided if the loop continues without stopping.. For internal workflows we have two things, ReAct agent ( AI Agent in qRaptor ) + Deterministic Flows ( Task Agent ) wherein we dont need reasoning loops..