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  # NCDTech β€” We design and research smart monitoring and control systems that grow.
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  Our roots are in smart monitoring and control.
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  With our robot simulation studio we stand on that extension line, and our AI sits on top of it.
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  What we build is the layer above that: self-inspection wired into every stage, and an on-premise LLM that reads those inspection records and explains them in plain conversation.
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  Making code verify itself is nothing new.
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  Test benches and unit tests live outside the code; self-checks live inside it: assertions, Design by Contract, and built-in self-tests (BIST/POST) are standard embedded practice.
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  The system grows through use, but only under administrator approval: code-based verdicts are never overwritten, every approved piece of knowledge keeps its full revision history, and nothing is ever silently deleted.
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  We do not so much invent new capabilities as put AI, without hesitation, on top of abilities we have already verified, and make it actually run.
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  **Current status**: first development phase complete, applied to our in-house autonomous driving simulator.
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  Demo application in progress, with the knowledge base still growing.
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  ---
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- ### ν•œκ΅­μ–΄
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  **NCDTech** β€” μ„±μž₯ν•˜λŠ” 슀마트 λͺ¨λ‹ˆν„°λ§ μ œμ–΄ μ‹œμŠ€ν…œμ„ μ„€κ³„ν•˜κ³  μ—°κ΅¬ν•˜λŠ” νšŒμ‚¬μž…λ‹ˆλ‹€.
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  데λͺ¨ 적용 쀑이며 지식은 ν™•μž₯ μ€‘μž…λ‹ˆλ‹€.
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  # NCDTech β€” We design and research smart monitoring and control systems that grow.
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+ ![NCDTech 4-layer stack](https://huggingface.co/spaces/NCDTech/README/resolve/main/assets/01_four_layer_stack.png)
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+ *(Diagrams and screens below are in Korean; they are the same figures used on our website and demo video.)*
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  Our roots are in smart monitoring and control.
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  With our robot simulation studio we stand on that extension line, and our AI sits on top of it.
 
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  What we build is the layer above that: self-inspection wired into every stage, and an on-premise LLM that reads those inspection records and explains them in plain conversation.
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+ ![An operator conversation with the on-premise LLM, captured as a knowledge record](https://huggingface.co/spaces/NCDTech/README/resolve/main/assets/02_llm_conversation.png)
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  Making code verify itself is nothing new.
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  Test benches and unit tests live outside the code; self-checks live inside it: assertions, Design by Contract, and built-in self-tests (BIST/POST) are standard embedded practice.
 
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  The system grows through use, but only under administrator approval: code-based verdicts are never overwritten, every approved piece of knowledge keeps its full revision history, and nothing is ever silently deleted.
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+ ![The administrator approval gate: accept, reject, or revise as a new revision](https://huggingface.co/spaces/NCDTech/README/resolve/main/assets/03_admin_approval.png)
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  We do not so much invent new capabilities as put AI, without hesitation, on top of abilities we have already verified, and make it actually run.
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  **Current status**: first development phase complete, applied to our in-house autonomous driving simulator.
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  Demo application in progress, with the knowledge base still growing.
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+ ![The in-house simulator: a tiny neural network driving in the 3D evaluation stage](https://huggingface.co/spaces/NCDTech/README/resolve/main/assets/04_3d_driving.png)
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+ ![The tracked test robot the simulator reproduces, with hand-mounted ultrasonic sensors](https://huggingface.co/spaces/NCDTech/README/resolve/main/assets/05_real_robot.jpg)
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  ---
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+ ## ν•œκ΅­μ–΄
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  **NCDTech** β€” μ„±μž₯ν•˜λŠ” 슀마트 λͺ¨λ‹ˆν„°λ§ μ œμ–΄ μ‹œμŠ€ν…œμ„ μ„€κ³„ν•˜κ³  μ—°κ΅¬ν•˜λŠ” νšŒμ‚¬μž…λ‹ˆλ‹€.
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  데λͺ¨ 적용 쀑이며 지식은 ν™•μž₯ μ€‘μž…λ‹ˆλ‹€.
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+ ---
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+ Website: https://www.ncdtech.org
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+ LinkedIn: https://www.linkedin.com/company/112725964
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+ Dataset: [NCDTech/human-gated-qaqc-knowledge-example](https://huggingface.co/datasets/NCDTech/human-gated-qaqc-knowledge-example) Β· Model: [NCDTech/sim-driving-mlp-numpy](https://huggingface.co/NCDTech/sim-driving-mlp-numpy)