Our technology comes from systems we built and run ourselves, not from other people's case studies. Here are our capabilities by field, and the lab where we prepare what comes next.
We build fast, lightweight static sites from a single data source and deploy them. From day one they are structured so search engines and AI can read them well.
We measure technical SEO and content, then track whether ChatGPT, Gemini, Perplexity and Naver's AI answers cite your site as a source.
We connect different AIs into one team. Agents such as Antigravity, Claude and Gemini exchange work through the command line (CLI) and our own message protocol, and split the stages of build, attack testing, defense and verification.
We wrap language models from different vendors behind one interface and switch between them by cost and purpose. AI calls between services go through a single gateway that checks signatures.
We deploy and run servers and databases across several clouds together with AI. AI handles routine checks; people approve changes and risky work.
We design flows so people no longer do repetitive work, while important decisions stay with people. Instructions go in and reports come back through a messenger.
We build SMS, KakaoTalk notification, email and sign-in as modules that are not tied to one provider. Switching providers leaves service code unchanged.
We attach a QR code to issued documents so recipients can confirm the original with a single scan. Only administrators register or revoke documents, and lookups trigger alerts.
We collect and clean scattered public and market data and turn it into a form you can decide with. Parsing is defensive so format changes do not break it.
From planning and generation to editing and publishing, we automate how blog posts and YouTube videos are made, together with AI. Items go out on schedule, and a person reviews them before they go public.
Topics we are testing first-hand on our YouTube channel “Doctor\'s AI Lab” (Korean). We try them small and expand what is proven.
Autonomous collaboration among AIs with split roles, plus task queue distribution
Document verification separated per organization
Academic database search, full-text parsing and embedding vector search
A short clinical record summarizer you can drop into other systems
Local model execution that keeps data on the machine
Small AIs trained for one specific purpose
Pose and hand recognition, plus network camera (PTZ) control
A macro engine that finds on-screen elements and operates existing programs
Recording and verifying AI work on a virtual PC, and guards that block dangerous commands
From still images to moving scenes
Give instructions and get results by voice, with speech recognition and synthesis
Tell us about your work. We will find the right combination together.
tech@coreaup.com