"The competitive standard for corporate AI is no longer which model to use, but how safely and consistently it can be operated in actual work environments," said Yang Young-mo, CEO of Redbrick. He explained that the early phase of generative AI focused on the performance of large language models (LLMs), but the emphasis has now shifted to the operational structure, which includes internal data, permissions, and security systems as key components of AI competitiveness.
Yang noted, "Initially, many questions revolved around 'which model to use,' but now there are far more operational questions such as 'Can we securely connect to our company data?' and 'How can we reflect departmental permissions?' Companies are beginning to view AI not just as a productivity tool but as an integral part of their operational infrastructure."
Redbrick, a startup specializing in generative AI-based content engines, offers AI solutions that support data and workflow automation for businesses and institutions through its proprietary 'Redbrick AI Engine.' The platform can generate content for games, education, and marketing with simple text inputs, and it integrates with internal documents and collaboration tools to assist with knowledge searches, document creation, and report drafting.
The enterprise solution, 'Redbrick AI Enterprise,' is available in both on-premises and cloud versions, ensuring secure handling of sensitive information through end-to-end encrypted inference structures. As of 2025, the company surpassed 10 million cumulative users and was selected for the UAE's Mubadala sovereign wealth fund startup incubation program, 'HUB71.'
Yang observed that corporate AI transformation (AX) projects are moving beyond simple chatbot implementations to the establishment of 'AI operational systems.' He explained that in practice, the structure of data, permission systems, and the redesign of work processes have become more critical than the performance of AI models. "In demo environments, AI appears to work well, but in actual corporate settings, documents are scattered across various systems, and both current and historical data are mixed. The complexity of the permission system means that simply attaching a model does not complete the AX process," he said.
As a result, Redbrick is expanding its focus from being just an AI solutions provider to becoming a 'corporate AI infrastructure platform' company. The core strategy involves securely connecting internal company data, operating AI agents tailored to departmental needs, and creating a structure for integrated management of data access permissions, costs, and logs.
Yang emphasized that the 'Front Deployment Engineer (FDE)' approach is becoming a significant trend in the global AI market. This method involves deeply engaging with clients' actual work environments to collaboratively define problems, rapidly implement solutions on the AI platform, and then enhance product features. He stated, "While past system integration projects were centered on requirements-based construction, FDE focuses on discovering problems together with clients on-site and accumulating them as repeatable platform features. Redbrick aims to be an AI engineering partner that designs AX transformations alongside our clients, not just a construction firm."
Another notable change is the shift of companies toward a 'Multi-LLM' operational system, where multiple AI models are used concurrently. This shift is driven by the varying costs, speeds, and inference capabilities required for different tasks, making it challenging to handle all operations with a single model. Yang remarked, "For simple summarization or classification, lightweight models are more efficient, while high-performance models are better suited for complex analysis or decision support. Ultimately, how AI is managed on an operational structure will become more important than the models themselves."
Looking ahead, Redbrick plans to focus on building an 'AI operational environment' that integrates AI infrastructure, knowledge-based AI, collaborative AI workspaces, AI workflow automation systems, and security, permission, and governance functions into a single corporate AI platform.
Yang concluded, "The corporate AI market will quickly transition from the experimental stage to actual operational implementation. Redbrick aims to grow as a platform company that helps organizations operate AI safely as an integral part of their work infrastructure, beyond mere usage."
* This article has been translated by AI.
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