AhnLab Cloudmate, which entered the cloud managed services provider (MSP) business in 2021, says it is confident of achieving a clear return to profit this year.

The MSP market is widely known as a business where growing sales does not necessarily make it easy to earn a profit. The company says it has grounds for emphasizing profitability: its own product strategy targeting the AI transformation (AX) market. The company plans to supply its in-house products to customers secured through its cloud MSP business, using that as a base to increase profit.

AhnLab Cloudmate CEO Hyung-jun Kim (김형준) and CTO Kwang-ho Choi (최광호) said in a recent interview with a reporter that the AX product business launched last year is already delivering results. They stressed that selling in-house products, rather than supplying foreign products, is bound to be more advantageous for profitability, and that parent company AhnLab has extensive experience developing products.

AhnLab Cloudmate's AX products are Secure Bridge, a generative AI security product, and ACMEi, a retrieval-augmented generation (RAG) solution.

Secure Bridge is designed to help companies use generative AI safely. It offers functions that address security gaps in generative AI environments with security and user convenience in mind, including detecting input and output of important data and preventing prompt injection, monitoring prompt history and controlling policies, and support for multiple LLMs and an agentless approach. It can be used in both cloud and on-premises environments.

Secure Bridge may look similar to existing data loss prevention (DLP) products, but its DNA is fundamentally different from simple DLP, Choi said. He said existing DLP solutions focus on preventing data from leaking from inside to outside, but Secure Bridge also checks data generated by AI. It prevents data risks in both directions regardless of whether data is internal or external, and can be used in natural language, he said.

AhnLab Cloudmate also equipped Secure Bridge with an in-house small language model (SLM). The AhnLab SLM understands users' natural-language questions and helps find whether there is leaked data. AhnLab Cloudmate unveiled Secure Bridge in June last year and secured a number of corporate customers. It believes a product strategy that considered usability also had a positive impact.

Kim said many other solutions force users to comply, which can reduce acceptance of security. He said the company also paid close attention to increasing security transparency when developing Secure Bridge.

AhnLab Cloudmate is also developing a next-generation version of Secure Bridge. The company expects the share of AI agents to increase. Choi said the goal is to go beyond Secure Bridge and serve as a hub in an agentic AI environment. He said it will be possible to securely verify information exchanged among AI agents.

AhnLab ACMEi is a platform that supports building AI assistants, enabling organizations to search internal data using LLMs. The company said ACMEi supports building AI assistants based on data customers have and data it provides. It provides a 'one-stop service' that supports building AI assistants such as AI chatbots optimized for internal environments, including building a customer-tailored data lake through automated data preprocessing, implementing AI assistants easily by providing basic templates, and supporting subscription-based security and integrated operations management services.

Many domestic and overseas products that claim to be RAG solutions are already on the market. In response, AhnLab Cloudmate stresses as a point of differentiation that ACMEi is product-based rather than a simple systems integration project. Kim said it supports customers in using AI easily and efficiently by building ACMEi based on specialized templates and solution foundations.

ACMEi is currently focused on supporting organizations such as government-funded research institutes in drafting reports and presentation materials, collecting research materials and comparing papers. The company plans to expand ACMEi into various fields beyond research institutions. Choi said it will actively leverage the advantage of being able to build RAG in a domain-specialized way based on templates.

According to the industry, there is also criticism that while the concept of RAG is attractive, it does not deliver as much effect in practice as expected. AhnLab Cloudmate says limitations in data access control are also among the causes, and it holds the view that using Secure Bridge and ACMEi together could help solve the problem.

Choi said RAG benefits from having a lot of data, but data access control is not easy. He said an architecture is needed that can use highly important data when needed and block it. He said combining Secure Bridge and ACMEi could solve such problems. The company also stresses synergy between its in-house AX solutions and its existing MSP business. Kim said increasing MSP customers remains important because it can supply AX solutions to those MSP customers. He said using AI can also improve the profitability of the MSP business.

AhnLab Cloudmate expects AX cases to increase this year that move beyond pilots and convert into actual projects. Kim said the real fight starts now. He said many RAG projects have been test projects so far, but this year there will be more attempts related to RAG and private LLMs. He said the company will use that as an opportunity to strengthen the positioning of its AX products.