Kaier CEO Kyohyuk Lee.
Kaier (CEO Kyohyuk Lee) develops and supplies a one-click AI automation MLOps solution that automatically trains optimal AI models. Kaier aims to help on-site experts in industrial environments—where it is challenging to assign dedicated AI specialists—use their own data to build AI models themselves. Through this, Kaier sets a goal to accelerate AI transformation across industries fundamentally.
Kaier’s one-click AI automation MLOps solution works in B2B and B2G settings across smart factories, social infrastructure operations, finance, marketing, and defense. Companies traditionally needed both AI researchers and on-site experts to adopt AI technologies, but Kaier aims to change that formula. On-site experts with internal operational, process, or image data can generate an optimized AI model that analyzes that data with one click and applies it immediately, without any AI technology knowledge.
CEO Kyohyuk Lee cites the shortage of AI talent as the biggest reason for the slow spread of AI across industries. Requirements and data structures differ by site, so companies had to assign AI researchers to each new project, which cost significant time and money. Even no-coding MLOps solutions on the market still require specialized knowledge to select model architectures or set up training environments during deployment, ultimately requiring an AI expert. Kaier’s solution removes these barriers entirely.
Using Kaier’s solution is simple. Users specify the directory where the training data is stored, then click the training start button. With only these two steps, the system automatically searches for the best AI model architecture for the data and completes an optimized model, including hyperparameters and training environment settings. Kaier’s target is an average training completion time of 15 hours. The company aims to offer an experience in which an on-site expert starts training at 6 p.m., then leaves work and finds a ready-to-use model when arriving at 9 a.m. the next morning.
Image provided by Kaier
Kaier first targets the vision AI sector. In smart factories, AI models that analyze images captured by cameras to distinguish between good and defective products are already widely used. Traditionally, factories needed internal AI teams or external specialists to design and train vision AI models after collecting large volumes of product images. With Kaier’s solution, quality managers or field engineers can gather product images and generate a good-versus-defective classification model with a single click, then link it to a real-time inspection system.
The solution also works widely for structured data analysis. Manufacturing processes involve sequential steps, and final product quality varies with the settings of process variables. When process data exists in table formats like Excel, Kaier’s solution trains an AI model from this structured data with one click to identify correlations between process conditions and product quality and suggest optimal settings that maximize good-product yield. The system uses data stored in ERP, MES, or simple Excel files, as long as the necessary information is available.
Kaier states that the one-click AI automation MLOps solution reduces AI adoption costs and time by up to tenfold. Traditional industrial infrastructure relied on statistics-based analysis, but Kaier sees deep learning-based AI technologies already achieving performance that is dozens of times higher than that of statistical methods. CEO Lee presents the company’s long-term vision as “replacing existing statistical technologies that support industrial infrastructure with artificial intelligence technologies as quickly as possible.”
CEO Lee’s background and market conditions motivated the founding of Kaier. He specialized in AI during his master’s and doctoral studies and worked as an AI expert for more than 25 years. In the mid-2010s, deep learning achieved a quantum leap in performance, reaching levels previously unimaginable. In Korea, government-led startup support programs expanded significantly, improving the startup environment. With market expectations rising sharply due to developments in large language models (LLMs) like ChatGPT, Lee felt it was the right time to build a solution that accelerates industry-wide AI transformation.
After building sufficient domestic references, Kaier plans to enter Southeast Asia and China first, where geographic proximity and strong manufacturing and industrial demand exist. The solution’s focus on data analytics allows broad applicability across global markets, regardless of industry or country.
Image provided by Kaier
Kaier also runs an LLM-based business separate from its one-click AI automation MLOps solution. Rather than competing directly with foundation model developers like OpenAI, the company focuses on building on-premises LLM infrastructure that enables clients to use internal data safely. Many companies want to generate reports, implement Q&A systems, or automate information retrieval using their internal documents and data, but cannot send confidential information to external cloud services. Kaier builds independent LLM environments inside client systems and customizes them to each company’s data and workflow as a system-integration-style service.
This area cannot yet achieve full one-click automation technically. Still, market research shows that the cloud-based and on-premises LLM markets are projected to grow at a similar rate, indicating strong potential. With capabilities in one-click MLOps automation and on-premises LLM infrastructure, Kaier plans to convert the massive data accumulated across industrial sites into real value.
Kaier continues to pursue a world where on-site experts—not AI specialists—lead AI utilization. Kaier envisions an industrial future where companies transition their statistical-era systems to AI-based infrastructure through one-click AI automation experiences.
Pangyo Techno Valley is a global R&D hub that integrates Research (R), People (P), Information (I), and Trade (T) across the IT, BT, CT, NT, and mobility sectors. It is a leading innovation cluster in Gyeonggi-do, established to drive technological innovation, talent development, job creation, and international business competitiveness.
The Gyeonggido Business & Science Accelerator’s Techno Valley Innovation Group has continuously promoted Pangyo Techno Valley’s value by hosting events such as the Pangyo Evening Meet-Up, Pan-Pan Day, Joy of Work in Pangyo, and Pangyo Startup Investment Exchange - In-Best Pangyo. These initiatives have facilitated networking between Pangyo companies, domestic and international investors, and the media. Similar events are planned for this year to support the growth and global expansion of Pangyo startups through various assistance programs.
