Meta has launched its paid artificial intelligence (AI) coding service, Muse Code, marking the company’s entry into the developer market.

On Aug. 5, Meta unveiled its latest Muse Spark 1.2 model alongside Muse Code, an AI coding agent. Muse Spark 1.2 is an updated version of the previous model optimized for software development tasks. According to Meta, the model was trained with significantly increased compute resources and a broader range of training environments, improving its capabilities in code generation, complex debugging and codebase comprehension.

While Muse Spark is a general-purpose model, Muse Code is a standalone terminal-based AI coding agent tool. Meta said it trained Muse Spark 1.2 and Muse Code together. Muse Code, the company’s first AI coding agent, is powered by the latest Muse Spark 1.2 model and has been released in beta for macOS and Linux.

One notable aspect of the announcement was the complete absence of references to open source. The shift is unusual for Meta, which has positioned itself as a leading advocate of open AI ecosystems in recent years.

Whereas the company previously pursued indirect monetization through the expansion of the open ecosystem around its open-weight Llama models, Muse Code represents an attempt to generate revenue directly from an in-house business.

Meta highlighted several technical features of Muse Code, including autonomous development workflows, persistent asynchronous background agents and local event logs.

An autonomous workflow feature allows the system to handle planning, coding, testing and result verification in a single process after receiving a user request—a standard capability among advanced AI coding tools. However, persistent asynchronous background agents represent Meta's key strategic move as a late entrant to the AI coding market.

Persistent background agents distribute workloads across multiple AI agents operating simultaneously in the background during a development session. While most competing AI coding tools also support background agents, those systems typically create new helper agents for each task.

In contrast, Muse Code keeps specialized background agents continuously active (warm) throughout an entire session. According to Meta, maintaining agents in a warm state rather than creating them for individual tasks helps avoid redundant information gathering.

This feature could significantly address practical inefficiencies in code development, as creating a new sub-agent for every task forces the system to repeatedly reread the same files.

Under this feature, large-scale tasks are distributed and processed in parallel by sub-agents operating within isolated Git worktrees. This architecture preserves the advantages of parallel execution while preventing state contamination, such as file deletion or modification by other agents on the same files.

Generally, a Git repository has only one working directory, but a Git worktree is a Git feature that enables multiple separate directories—each checking out different branches—to share a single repository (.git history) simultaneously. Each sub-agent operates within its own worktree (an independent directory with an independent branch), ensuring physical isolation from file changes made by other agents. Once work is complete, branches can be merged sequentially, confining conflict management strictly to the integration phase.

Although the technology itself is not new, many products still process subtasks sequentially within a single worktree or rely on file locking and execution ordering for parallel processing. Adopting worktree isolation as a core architecture increases implementation complexity and cost, requiring branch creation and management, merge strategies, conflict handling and cleanup logic.

For that reason, technology media outlet VentureBeat praised Meta’s decision to offer the architecture as a built-in capability at the harness level, despite its relatively limited adoption across the industry.

Meta also highlighted its local event log system, which records model calls, tool usage, approvals and code edit histories to enable task resumption even after crashes. The append-only event log allows developers to replay their entire work history from start to finish to resume work following a failure. This substantially resolves operational issues and serves as a foundation for audit trails.

Overwrite-style event logs make it impossible to determine prior actions, the process taken to reach the current state, or pending tasks. In contrast, foreign media outlets have praised Muse Code's append-only event log system for preserving the entire history sequentially for reconstruction at any time. This forms the foundation for developer efficiency, operational problem-solving, failure recovery and root-cause analysis (RCA) audit trails.

However, Muse Code does have weaknesses. First, its initial release is restricted to a terminal interface. Competing products such as Anthropic’s Claude Code offer terminal, IDE, desktop and web interfaces, while OpenAI’s Codex is supported across CLI tools, IDE extensions and cloud services.

Meta also released benchmark results comparing Muse Spark 1.2 and Muse Code against competing AI models, including Grok 4.5, Claude Opus 5, GPT-5.6 Terra and Gemini 3.6 Flash. The choice of comparison models sparked controversy, as Meta avoided top-tier models from competitors in favor of second-tier options.

According to Meta, Muse Spark 1.2 and Muse Code (harness) achieved a score of 82.9% on Terminal Bench 2.1, narrowly outperforming OpenAI’s GPT-5.6 Terra and Codex at 81.8% and SpaceX (xAI)’s Grok 4.5 and Grok Build at 81.6%. However, it trailed Anthropic’s Claude Opus 5 and Claude Code, which scored 86.7%.

On the Deep SWE 1.1 benchmark, Muse Spark 1.2 ranked behind Claude Opus and OpenAI GPT-5.6 Terra. This drew criticism from the developer community, with some arguing that the system would show lower performance when compared against GPT-5.6 Sol.

AI tech news site Kingy AI further claimed that Meta’s reported benchmark scores were slightly higher than actual verified figures, publishing a side-by-side comparison between Meta’s claims and verified evaluation scores.

The timing of the announcement has also raised suspicion. Muse Code was unveiled less than a month after the release of Muse Spark 1.1. Observers interpret this as an attempt by Meta to regain momentum after Moonshot AI’s Kimi K3 stole the spotlight with overwhelming performance immediately following the ambitious Muse Spark 1.1 launch.

Despite these concerns, Muse Code’s pricing structure is viewed as a major advantage that offsets doubts about its market positioning. Meta is attempting to compensate for its late entry into the coding tool market with an aggressive pricing policy.

Critics note that the pricing strategy is more disruptive than the technology itself. Under the Standard Tier, Muse Spark 1.2 API access for Muse Code costs $1.25 per million input tokens and $4.25 per million output tokens, with cached inputs priced at $0.15 per million tokens. Meta also pledged not to use prompts or generated outputs for model training.

A second pricing option, the Contributor Tier, is available at just $0.10 per million input tokens and $0.20 per million output tokens. In exchange, developers must allow Meta to use their code for future model training.

Financial pressure appears to be driving this aggressive pricing strategy. While Meta reported second-quarter revenue of $60.8 billion, up 28% year over year, operating income fell 8% to $18.8 billion, and operating margin declined from 43% a year earlier to 31%. Capital expenditures (CAPEX) reached $31.08 billion for the quarter alone, with full-year guidance reaching up to $145 billion.

Meanwhile, entering the developer market effectively means entering the enterprise market. Alexander Wang, chief AI officer (CAIO) of Meta Superintelligence Labs and head of Muse Code development, emphasized the product's enterprise capabilities, noting that requests for Zero Data Retention (ZDR) features have already begun arriving. Remarks from CAIO Alexander Wang suggest that ZDR is currently implemented in Muse Code as an optional capability available to enterprises upon request.

ZDR is an agreement where the AI service provider immediately deletes user inputs (prompts) and outputs (responses) from servers upon completion of API call processing, storing them in no form whatsoever. While the Standard Tier already includes a commitment not to use prompts and data for training, ZDR goes one step further.

Under standard tiers, logs are temporarily stored on servers for a set period before deletion, whereas ZDR prevents storage entirely from the outset, eliminating risks associated with data leaks, hacking or future legal disputes. This is essential for regulatory compliance and intellectual property (IP) protection, both of which are major hurdles for enterprise adoption of AI coding tools.

Organizations handling sensitive source code representing trade secrets or operating under strict legal requirements regarding data retention on third-party servers demand ZDR capabilities. Without ZDR, deployment in highly regulated industries remains difficult regardless of model performance, making the feature an essential requirement for AI models and coding tools targeting the enterprise market.

Kakao plans to introduce an agentic artificial intelligence (AI) service that can identify food-ordering intent within KakaoTalk conversations and connect users from menu recommendations to payment through a partnership with Coupang Eats.

The company disclosed during its second-quarter 2026 earnings conference call on Aug. 6 that it has signed an agent-to-agent (A2A) partnership agreement with Coupang Eats. Under the envisioned model, KakaoTalk’s on-device AI will analyze conversational context and user preferences to recommend menu items, while the Coupang Eats agent will handle ordering and payment functions.

The two companies are currently discussing implementation details. Beginning with food delivery, Kakao plans to expand its agentic AI ecosystem into other frequently used consumer services, including commerce, reservations, travel and payments.

KakaoTalk will incorporate the company’s on-device AI model, Kanana 2 1.3B, along with long-term memory technology. The system is designed to understand schedules and interests scattered across multiple conversations as a unified context and provide increasingly personalized services based on accumulated user behavior and preferences. Kakao plans to introduce related experiences gradually in the second half of the year and is targeting more than 10 million monthly active users (MAUs) for its AI services by year-end.

Kakao said it will focus its resources on AI services that directly interact with consumers rather than infrastructure businesses such as AI data centers, graphics processing units (GPUs) and cloud computing. The company believes large upfront investments and ongoing capital expenditures are required for AI infrastructure, while rapid technology refresh cycles for GPUs and AI servers make the long-term sustainability of current profitability uncertain.

As a result, Kakao intends to prioritize AI services at the user interface level rather than capital-intensive infrastructure investments. The company plans to strengthen its in-house capabilities across the AI value chain, from models to services, leveraging its strengths in business-to-consumer (B2C) platforms.

Kakao reported second-quarter revenue of 2.0985 trillion won and operating profit of 277.0 billion won, both record highs for a single quarter. The figures increased 9% and 36%, respectively, from a year earlier.

Revenue from the platform segment rose 17% year over year to 1.2303 trillion won. Talk Biz revenue reached 643.2 billion won, while advertising and subscription revenue hit a quarterly record of 399.9 billion won. Business messaging revenue and display advertising within KakaoTalk grew 20% and 28%, respectively.

Revenue from the content segment totaled 868.2 billion won, remaining broadly in line with the previous year. Music and media revenue increased, while story revenue declined 16%.

“Considering the direction of Kakao’s AI strategy and the speed of execution, we expect the foundation for AI mass adoption to be established by the end of this year and full-scale monetization to begin next year,” Chief Executive Officer Chung Shin-a said.

Kakao aims to increase the share of AI-related revenue within its Talk Biz segment to double-digit percentages by 2028 through transaction fees, subscriptions and AI-powered advertising, positioning AI as a key driver to reignite Talk Biz growth and serve as a major revenue source.

Kakao reported record quarterly revenue and operating profit for the second quarter, driven by continued growth across its platform businesses. Strong performance from Talk Biz, mobility and payments operations also strengthened the company’s financial capacity to invest in artificial intelligence (AI) initiatives.

The company said on Aug. 6 that second-quarter revenue reached 2.10 trillion won, while operating profit rose to 277.0 billion won on a consolidated basis under Korean International Financial Reporting Standards (K-IFRS). The figures were up 9% and 36%, respectively, from a year earlier.

Revenue from the platform segment totaled 1.23 trillion won, an increase of 17% year over year. Within the segment, Talk Biz generated 643.2 billion won, accounting for 52% of platform revenue. Advertising and subscription revenue rose 14% from a year earlier to 399.9 billion won.

Business messaging revenue increased 20% as demand from advertisers in the financial sector expanded. Display advertising on KakaoTalk also grew 28%, supported by higher user engagement and the performance of new advertising products.

Talk Biz commerce revenue reached 243.2 billion won, up 10% from the same period last year. Combined gross merchandise value from services including Gift and Talk Deal increased 9% to 2.7 trillion won during the quarter. Self-purchase transactions through the Gift platform rose 39%.

Revenue from other platform businesses, including mobility and payments, climbed 22% year over year to 587.0 billion won. The mobility business benefited from growth in its core operations and last-mile logistics services. Kakao Pay posted record quarterly revenue and operating profit, supported by higher financial-service revenue and growth in payment and platform services.

Revenue from the content segment increased 1% from a year earlier to 868.2 billion won. Music revenue rose 8% to 558.4 billion won, while media revenue increased 5% to 99.1 billion won. Story revenue totaled 210.7 billion won.

Operating expenses rose 6% year over year to 1.82 trillion won.

Kakao said it plans to gradually introduce agentic AI services within KakaoTalk that connect everyday activities such as ordering, reservations and payments. The company will work with partners in commerce, reservations, travel and payments while expanding its ecosystem through its open platform, PlayMCP.

As an initial example, Kakao plans to establish an environment in which users can complete food ordering and payment directly within a KakaoTalk chat room through an agent-to-agent (A2A) partnership with Coupang Eats. The company said an on-device AI model will understand conversational context and seamlessly connect users to ordering and payment functions.

Canadian enterprise AI company Cohere held its first media briefing in South Korea on Aug. 5 at The Westin Josun Seoul, unveiling plans to make the country a key hub for its Asia-Pacific expansion. Frank O'Dowd, Chief Revenue and Commercial Officer, and Hugh Jang, President for Asia-Pacific, outlined the company's regional strategy.

O'Dowd said South Korea is the most dynamic and competitive AI market in the Asia-Pacific region, adding that success in Korea would provide a strong foundation for expansion into other regional markets. Based on that assessment, Cohere plans to establish a Korean subsidiary by the fourth quarter of this year and hire a double-digit number of technical and sales personnel. The company also plans to establish a separate legal entity in Japan and deepen cooperation with Fujitsu, while expanding support for public-sector customers in Singapore.

Cohere's business in South Korea has expanded through its partnership with LG CNS. The company described LG CNS as its first key partner in the market, helping localize Cohere's AI models and agentic AI platform for Korean language and industry requirements. Cohere said it plans to broaden its domestic ecosystem beyond LG CNS to include additional IT service providers and AI model companies.

Two themes stood out in Cohere's presentation. First, the company spent considerably more time discussing its AI agent platform, North, than its proprietary generative AI model family, Command. Second, it positioned sovereign AI as a core competitive advantage.

Cohere was originally known for developing the enterprise large language model (LLM) Command. Founded in 2019 with the goal of building generative AI for businesses, the company counts Aidan Gomez among its three co-founders. Gomez, formerly of Google Brain, was a co-author of the landmark 2017 paper "Attention Is All You Need," which introduced the Transformer architecture that underpins modern AI and LLMs.

From the outset, Cohere targeted enterprise customers. It launched API services for enterprise text generation and vector embeddings in 2021 and later developed Command in 2022. Until the launch of North in January last year, the company's primary focus was AI models. At its first Korean press event, however, the majority of the discussion centered on North, its AI workspace platform.

North is an enterprise AI agent platform that connects internal corporate data and business systems so AI agents can perform real-world work tasks. Combined with Cohere's Embed and Rerank engines, it enables retrieval-augmented generation (RAG)-based search across large volumes of enterprise data, including documents, emails, databases and wikis, allowing users to find relevant information and generate answers and reports. The platform also supports enterprise AI agents capable of autonomously planning and executing multi-step tasks and workflow automation.

When Cohere launched North early last year, it positioned the product as an enterprise alternative to Microsoft and Google. North competes directly with Microsoft Copilot Studio and Google Vertex AI Agent Builder.

All three platforms connect enterprise data such as documents, emails and presentation files with AI systems to create customized internal AI agents.

Microsoft Copilot Studio is tightly integrated with the Microsoft 365 ecosystem, making it highly accessible for enterprises running Windows-based environments. Google Vertex AI Agent Builder allows organizations to build agents integrated with Google Workspace on Google Cloud Platform infrastructure.

In contrast, Cohere said North is not tied to any specific hyperscale cloud ecosystem and can be deployed across any cloud platform or internal infrastructure chosen by the customer. The company argues that this flexibility makes North particularly suitable for organizations that seek independence from large technology vendors and require stronger security controls and customization, especially in financial services and other highly regulated industries.

According to Cohere, the company has adhered to four principles since its founding: enterprise control of data, multi-cloud support, on-premises deployment capability, and strong security and privacy protection. Command and North can be deployed in public clouds, private cloud environments, customer-owned data centers, or air-gapped environments disconnected from the internet. The company cited this deployment flexibility as its primary differentiator and the foundation of its sovereign AI strategy.

Cohere argued that enterprises and government agencies should be able to maintain direct control over both their data and AI operating environments. The company said its ability to support AI deployment in private cloud and on-premises environments, in addition to public cloud infrastructure, enables customers to meet data sovereignty and security requirements.

According to international media reports including TechCrunch, overseas customers using North have adopted the platform's agent capabilities in on-premises environments to balance strict security requirements with business productivity gains. Royal Bank of Canada (RBC), for example, worked with Cohere to develop and deploy North for Banking, a dedicated platform tailored to financial services. All financial data remains within RBC's own data centers and is not transmitted to external cloud environments.

LG CNS is also cited as one of North's key early customers. Cohere and LG CNS signed a partnership agreement in March 2025, and Cohere later stated on its corporate blog that LG CNS had deployed North to validate the effectiveness of AI agents in large-scale enterprise environments. According to the company, the platform is being used as a foundation for secure, customized AI agent initiatives at Korean enterprises that are highly sensitive to data leakage risks and seek alternatives to dependence on major technology vendors.

Cohere also said North provides transparent citations to source documents and visibility into how responses are generated, allowing enterprises to trace AI-generated outputs. The company said these capabilities have made the platform particularly attractive to financial institutions and large enterprises where controlling hallucinations is critical.

O'Dowd said many organizations have adopted generative AI but have not achieved the return on investment they initially expected. Rather than relying on the largest available AI models, he said, companies should select models suited to specific business objectives and optimize both performance and cost.

As part of that strategy, Cohere said North supports not only the company's own Command models but also a range of third-party AI models. The company also emphasized that it charges customers based on the number of annual users rather than token consumption, making AI operating costs more predictable for enterprises.

Cohere's decision to place North ahead of Command appears to reflect a recognition that competing solely on model performance is no longer sufficient. When Command was first introduced, model-to-model performance competition was still a meaningful differentiator. Today, however, the company lacks a model that directly rivals the performance of OpenAI's ChatGPT or Anthropic's Claude.

Instead, Cohere argues that enterprises should have broad freedom to choose the most appropriate models for their environments, including open-weight models, and describes that model choice as another component of sovereign AI. The message closely mirrors comments recently made by Palantir Chief Executive Officer Alex Karp.

In terms of market positioning, strategic direction and enterprise deployment scope, Cohere North sits between Palantir AIP and OpenAI's ChatGPT Enterprise and ChatGPT Work offerings. The distinctions among the three platforms, however, are becoming increasingly blurred.

OpenAI is expanding beyond AI assistants toward AI agent platforms and enterprise workflow automation, while Palantir is broadening AIP beyond operational automation into knowledge-worker functions such as document processing and natural-language interfaces. Cohere occupies a position that gives it opportunities to expand in both directions, but also leaves it exposed to competitive pressure from both sides.

Bigwave Robotics and Omron Electronics Korea have signed a memorandum of understanding (MOU) to cooperate in the robotics business, aiming to establish a framework for deploying safe humanoid robots in industrial environments.

Bigwave said that while humanoid robot pilot projects are expanding, existing robot safety standards do not adequately account for characteristics such as bipedal locomotion and AI-based autonomous decision-making. As a result, the company said there is a growing need to integrate risk assessment and safety design from the earliest stages of humanoid robot deployment.

Under the agreement, Bigwave's humanoid robot supply and system integration capabilities will be combined with Omron Electronics Korea's industrial safety consulting and safety control technologies to establish new safety standards for humanoid robots.

The two companies plan to jointly manage the entire process, from identifying customer demand and proposing robot specifications to risk assessment, safety hardware design and installation, validation, and documentation. Bigwave will propose humanoid robots and systems tailored to customer manufacturing processes and oversee on-site integration.

Omron Electronics Korea will support risk assessments and Performance Level required (PLr) analysis based on ISO 12100 and ISO 13849-1 standards, as well as the deployment of safety solutions including safety programmable logic controllers (PLCs), emergency-stop switches, and laser scanners. When necessary, the company will also integrate safety hardware such as light curtains, which stop equipment operation when a worker enters a monitored area, and door switches to improve applicability in industrial settings.

Bigwave said customers will be able to receive robot supply, safety consulting, safety hardware deployment, validation documentation, and on-site implementation as part of a single project. To accelerate humanoid robot adoption in manufacturing and logistics facilities, the company will establish a demonstration environment for safety solutions at its data center, where the partners will conduct joint proof-of-concept (PoC) projects and field trials.

The companies also plan to standardize processes from initial consultation through on-site deployment and secure real-world implementation references through joint seminars and facility assessments.

AI platform company INFINIQ has begun developing an intelligent data processing technology that converts handwritten military logistics documents into AI-based digital data.

The company announced that it has completed the project kickoff for the development of an OCR-based intelligent data processing and structuring system for unstructured handwritten documents in the military logistics sector under the second round of the 2026 SME Technology Development Support Program. Delivery is scheduled for December.

The project's core objective is to automatically recognize unstructured logistics documents—including supply requisition forms, maintenance records and inventory status reports—using AI-powered optical character recognition (OCR) and convert them into structured data that can be directly linked to the Defense Logistics Integrated Information System (DELIIS).

INFINIQ said most military logistics forms are currently handwritten and later re-entered manually by personnel, resulting in significant labor consumption and data-entry errors. The company added that conventional OCR solutions relying on external cloud APIs have limitations in accurately recognizing military-specific codes such as National Stock Numbers (NSNs) and unit abbreviations.

To address these challenges, INFINIQ plans to deploy a three-layer hybrid recognition engine combining precision OCR, visual language model (VLM)-based contextual understanding and ontology-based logical validation. OCR will recognize handwritten text and special codes, the VLM will correct misidentified content based on context, and the ontology layer will verify data consistency according to military logistics domain rules.

The company said the system is designed to achieve character recognition accuracy exceeding 95%, a character error rate (CER) below 5%, and processing times of less than five minutes per document. INFINIQ emphasized that the platform will operate independently within a fully isolated on-premises network without external internet connectivity, and will also incorporate a five-layer security framework that includes data encryption, role-based access control and automatic masking of personal information.

According to the company, the system will enable personnel currently assigned to manual data entry to focus on analytical and decision-making tasks while reducing data entry and verification time by more than 50%. The company added that the accumulated maintenance data could later be analyzed using time-series techniques to predict optimal maintenance schedules, which could reduce maintenance costs, prevent equipment failures and improve overall logistics operations.

To ensure technical completeness and domain relevance, the Korea Military Academy will participate as an advisory institution. The academy will provide development facilities and collaborate throughout the project on ontology design and validation.

INFINIQ also plans to integrate the structured logistics data generated by the project with its ontology-based decision support platform, AURON. Combined with AURON, the data can be searched and analyzed through semantic relationships linking maintenance histories and inventory status, and the platform can assess impact ranges and maintenance priorities based on relationships among equipment, units and supplies. The company said it ultimately plans to visualize the data through dashboards and expand the system into a military-specific AI platform that can be utilized across units, facilities and operational functions.

CJ ONE, the lifestyle membership platform operated by CJ OliveNetworks, is launching its August Wonder Series promotion in partnership with Mega MGC Coffee.

The company previously held the promotion with Tous Les Jours in July and will offer benefits through Mega MGC Coffee in August.

The August Wonder Series consists of Wonder Week with Mega MGC Coffee, Wonder Raffle on Aug. 11 and Wonder Quiz on Aug. 21.

Wonder Raffle will offer prize drawings, while Wonder Quiz will provide opportunities to earn CJ ONE points and benefits from major CJ brands.

From Aug. 1 to Aug. 5, CJ ONE is running a teaser event for Wonder Week. Members who sign up for event notifications through the CJ ONE app during the period will receive CJ ONE points.

The main Wonder Week event will run from Aug. 6 to Aug. 10.

During the event, all CJ ONE members can receive a 50% discount coupon for a Mega MGC Coffee iced Americano through the CJ ONE app at 10 a.m. each day.

Members who did not earn or redeem CJ ONE points at Mega MGC Coffee between Jan. 1 and July 31, 2026, will receive an additional 50% discount coupon if they make their first point transaction during the Wonder Week promotion.

Com2uS' upcoming MMORPG Zeus: The God of Arrogance (Zeus) and Smilegate's Eclipse: The Awakening (Eclipse) are set to face off in the market with launches just two weeks apart. While both games aim to reduce the fatigue associated with long play sessions in traditional MMORPGs, they differ significantly in their settings, competitive structures and character progression systems.

Published by Com2uS and developed by AButton, Zeus is scheduled for release on Aug. 26. Eclipse, published by Smilegate and developed by NPIXEL, is slated to launch on Sept. 10.

Zeus is built around a world inspired by Greek mythology. Rather than directly adapting familiar myths, the game reimagines the stories of Pandora, the Titans and the Olympian gods in a world fractured by the arrogance of Zeus, the king of the gods. Unreal Engine 5-powered graphics and a multilayered competitive structure are among its key features.

"Greek mythology is a story that virtually everyone knows, yet it has surprisingly rarely been explored properly in games," said Jung Sung-hoon, director at AButton. "We used that familiarity as a starting point while adding our own fresh elements. Many well-known gods will guide players into the world of the God of Arrogance, each with their own role."

In contrast, Eclipse adopts an original setting centered on the prosperous world of Ederion, blessed by the gods, and its hidden counterpart, Orthea. The game builds its own narrative around uncovering the truth concealed behind a seemingly perfect world.

"Stories based on well-known mythological elements often have predefined events, narratives and character frameworks," said Kim Dong-hyuk, chief art director at NPIXEL. "Rather than incorporating existing mythology, we felt it was important to create our own mythological details, which is why we chose an original story."

At the core of both games is the effort to reduce the burden of extended MMORPG play. However, Zeus focuses on improving convenience so that more players can participate in competition and progression, rather than reducing competitive elements themselves. Even while using AI-driven auto-play mode, players can access shops, trade items and manage equipment. A scheduling function also allows players to assign different hunting areas based on time periods.

The game also introduces an AI-powered "Persona" system designed to lower playtime requirements while preserving the appeal of competitive MMORPG gameplay. Personas are AI-controlled replicas generated in real time using a player's character specifications and appearance. Players can compete against these personas in one-on-one content such as the Colosseum and in large-scale guild-versus-guild RvR content known as the Arcadia Festival.

Eclipse, meanwhile, defines its approach as "MMO Lite." The concept aims to preserve the enjoyment of progression, cooperation and combat while reducing both time and spending requirements. Its flagship "Sanctuary" feature allows players to accumulate experience points and growth resources even while offline. The game also includes an AI mode that enables automated hunting during offline periods and a support feature called "Eclipse Time," which lets players choose their preferred play schedule.

The two titles also differ in their player-versus-player (PvP) philosophies. While Zeus emphasizes a multilayered competitive structure, Eclipse adopts optional PvP, giving players greater control over whether they participate in competitive content. Most areas are designated as safe zones, and large-scale battles are designed to be completed in shorter sessions. Combat strategies based on weapon selection and skill combinations further distinguish the game.

Both titles are strategically important to their publishers' MMORPG businesses. Zeus is Com2uS' flagship MMORPG release for the second half of the year and the first title from AButton. With The Starlight, released in 2025, falling short of expectations, industry observers are watching to see whether Zeus can become a new growth driver for the company's RPG business.

Eclipse is a new MMORPG jointly introduced by Smilegate and NPIXEL. As revenue from Lost Ark continues to stabilize at lower levels, the title is expected to play a key role in securing new revenue streams. Industry attention is also focused on how players will respond to the game's "MMO Lite" strategy, which seeks to maintain traditional MMORPG progression and competitive systems while reducing player burden.

By taking different approaches to easing MMORPG fatigue—Zeus through Greek mythology and competitive gameplay, and Eclipse through an original world and optional PvP—the two titles are poised to compete for different segments of the market. Their launches, separated by roughly two weeks, will be closely watched in the second half of the year.

Woowa Brothers, the operator of food delivery platform Baemin, said on Aug. 10 that it signed a memorandum of understanding with South Korea's Ministry of the Interior and Safety to promote the use of certified low-price businesses, known as Good Price Stores.

Good Price Stores are businesses recognized by the ministry and local governments for offering affordable prices, hygienic environments and friendly service, making them establishments that consumers are likely to revisit.

The agreement is intended to help ease the burden of inflation on consumers. Under the program, restaurant owners who have maintained affordable prices will gain additional opportunities to increase sales, while consumers will receive benefits through the Baemin platform.

From Aug. 17 through Sept. 13, customers will be able to receive delivery-only discount coupons worth 3,000 won for orders placed at participating Good Price Stores on a first-come, first-served basis.

Baemin will also support participating businesses by featuring them through banner promotions on the "Together Store" page within its mutual-growth program section on the platform.

Global AI audio research startup ElevenLabs has made its new dubbing model, Dubbing v2, available through its ElevenAPI platform, allowing developers to integrate the technology directly into their products and workflows. The model was first introduced through a user interface version in May and is now being offered via API access.

Unlike conventional dubbing systems that follow a speech recognition → translation → speech synthesis pipeline using cloned voices, Dubbing v2 employs a direct speech-to-speech (audio-to-audio) architecture. ElevenLabs said the model generates speech output directly from the source speech, enabling it to replicate the speaker's voice and more faithfully reflect the original's emotional expression and performance while producing natural multilingual dubbing.

The company also said the model is designed to align spoken dialogue naturally with video timing, improving synchronization accuracy. However, Dubbing v2 does not provide AI lip-sync processing for video content or real-time multilingual dubbing for live-streamed broadcasts. The model supports 92 languages, including Korean.

ElevenLabs said the primary target users for Dubbing v2 include content creators, media companies and global enterprises seeking to deliver high-quality content to international audiences.

The company added that professional film- and television-grade dubbing has traditionally cost hundreds of dollars per minute, whereas Dubbing v2 aims to provide high-quality dubbing at a more affordable price point.

MICUBE Solution, a provider of smart factory and autonomous manufacturing artificial intelligence (AI) solutions, will build an AI autonomous manufacturing platform for cosmetics original development manufacturer (ODM) Cosmecca Korea.

The project is being carried out under the Ministry of SMEs and Startups' "AI Applied Product Rapid Commercialization Support Program," operated by the AI Innovation Promotion Team of the Korea Technology and Information Promotion Agency for SMEs (TIPA). MICUBE is one of the selected solution providers for the initiative.

MICUBE will develop five core AI solutions to be deployed at Cosmecca Korea's manufacturing facilities. The goal is to create an intelligent autonomous manufacturing environment spanning the entire cosmetics production process, from research and development to formulation, production and quality inspection.

The solutions include: an AI Multi-Vision Quality Inspection system that uses deep-learning-based image analysis to respond immediately to product diversification and process changes; a Recipe Generation AI system that analyzes body and skin information alongside raw material and ingredient data to recommend optimal cosmetic formulations and validate them in a virtual environment; a Similar Complaint Prevention AI system that leverages large language models (LLMs) to analyze historical quality and customer complaint data, predict potential defects and provide natural-language question-and-answer capabilities; a Generative AI Data Integration platform that connects data across R&D, production and quality processes to support real-time decision-making; and a Digital Twin-Based Autonomous Control system that combines virtual manufacturing environments with LLMs to optimize processes in real time while providing AI-generated control recommendations and decision rationales.

Regarding the Recipe Generation AI solution, MICUBE said it has already validated a mathematical structure-based optimization algorithm in the secondary battery industry, where it analyzes large numbers of raw material combinations to identify optimal formulations. The company plans to apply that technology to cosmetics recipe development. It added that it has carried out numerous AI projects in industries such as food and chemicals, where ingredient blending and recipe optimization are critical.

The project will be implemented over two years. During the first year, the companies will establish AI core models and data infrastructure. In the second year, they plan to enhance the AI models, conduct field validation and commercialize a customized autonomous manufacturing system. The companies also intend to expand deployment of the solutions to Cosmecca Korea's global production sites.

MICUBE said it aims to successfully demonstrate a cosmetics-focused AI integration framework that combines generative AI and digital twins through the project. The company plans to expand the framework as a standard AI transformation (AX) model for small and mid-sized manufacturers and broaden the application of its autonomous manufacturing solutions to industries including pharmaceuticals and biotechnology.

Webzen on Aug. 10 revealed the first gameplay visuals and details for its self-developed upcoming title, Project D1.

Project D1 is a command strategy role-playing game (RPG) being developed by Webzen Crevix, a subsidiary of Webzen, based on the intellectual property (IP) of the popular webtoon I Became the Tyrant of a Defense Game. The title is currently in development with a target launch in 2027.

The game recreates the world into which the protagonist of the original webtoon is summoned, using a dot-graphics-based "diorama pixel art" style. The technique combines 2D pixel art with three-dimensional spatial presentation.

The original webtoon's narrative has been adapted into a party-based combat system. The episodes and storylines involving the protagonist have been reinterpreted through party composition, tactical operations, character progression and command-based battles.

Webzen said it plans to disclose more detailed information about the game in the second half of this year.

Chinese AI startup DeepSeek and robotics manufacturer Unitree are partnering to develop AI models for robots.

According to Reuters and other media reports on Aug. 6, DeepSeek will invest 140.8 million yuan in Unitree and receive 933,399 shares, equivalent to a 2.31% stake, through a strategic allocation tied to Unitree's initial public offering (IPO) in Shanghai. The companies plan to use the partnership to develop robotics AI. DeepSeek will contribute AI model development capabilities, while Unitree will provide expertise in mechanical engineering, motion control and embodied intelligence.

Specific details about the robotics models under development have not been disclosed. However, the South China Morning Post reported that the two companies will jointly develop not only AI models but also embodied AI technologies, while granting each other preferential access. Unitree will give priority to DeepSeek when procuring AI models and model-training services, while DeepSeek will prioritize Unitree when purchasing humanoid robots, quadruped robots and robotics platforms.

Unitree's robotics data and hardware platforms are expected to become key assets for DeepSeek's robotics AI ambitions. For Unitree, access to advanced robotics AI models could strengthen its competitive position against AgiBot. More broadly, the partnership could help China combine its strengths in humanoid robot hardware, supply chains and manufacturing capacity with frontier AI models.

Reuters noted that while Chinese humanoid robots are relatively inexpensive and capable of complex movements, they still lack the autonomy needed to perform real-world tasks without human intervention. The combination of Unitree's physical-world data and DeepSeek's AI expertise could improve competitiveness in the humanoid robotics model market.

The "brains" of humanoid robots are typically powered by Vision-Language-Action (VLA) models, World Models (WMs) or Robot Foundation Models (RFMs). Prominent examples include Gemini Robotics from Google DeepMind, GR00T from Nvidia, Helix from Figure AI and π0 from Physical Intelligence.

Chinese-developed robotics models include proprietary systems used by robot makers such as Unitree and AgiBot, as well as ByteDance's GR-3 and GR-RL, Tencent's Hy-Embodied-VLM and Alibaba's RynnVLA-001.

The evolution of robotics AI depends heavily on physical-world data used for training. Given China's rapidly growing humanoid robot shipments, the industry could benefit from a virtuous cycle of model development, data collection and model retraining. Considering Unitree's market position, data collected from its deployed robots may significantly accelerate DeepSeek's robotics AI development.

According to market research firms, the global humanoid robot market is currently dominated by China's AgiBot and Unitree.

Omdia estimates that AgiBot shipped 5,168 units in 2025, representing 39% of the global total of 13,000 units, while Unitree shipped 4,200 units, accounting for 32%. Counterpoint Research estimates a larger market of roughly 16,000 units, with AgiBot holding a 31% share and Unitree 27%.

By contrast, China's CCID (China Center for Information Industry Development) ranked Unitree as the market leader with a 32.4% share. Unitree has stated that its actual humanoid robot sales and shipments exceeded 5,500 units in 2025, a figure included in its IPO prospectus.

Even if AgiBot remains the leader, the shipment gap between the two companies is only around 330 units according to Omdia's estimates. In an early-stage market totaling approximately 13,000 to 18,000 units annually, such differences are small enough for rankings to vary depending on methodology.

AgiBot's developer, AgiBot Innovation Technology, was founded with the goal of developing general-purpose embodied AI robots. The company has built a vertically integrated portfolio covering robot hardware, components, robotics AI models, VLA and embodied AI models, robot data collection platforms and training datasets.

In March 2025, AgiBot introduced its GO-1 embodied AI foundation model, followed by WholeBodyVLA in December. It also built a large-scale robotics data platform called AgiBot World, which reportedly contains more than one million robot manipulation trajectories across 217 tasks.

As a result, Unitree has generally been viewed as a company with strong robot manufacturing capabilities and a cost advantage, while AgiBot has been seen as a provider of integrated robot hardware, data and embodied AI. The DeepSeek-Unitree partnership could blur that distinction.

Unitree is also developing embodied AI models internally and is reportedly training robot behaviors in simulation environments.

A report published in April by the Mercator Institute for China Studies (MERICS) said Unitree has been using Nvidia Isaac Lab to train robots for complex behaviors. Unitree's IPO prospectus also states that 48% of the funds raised through the IPO will be invested in embodied AI model training. The company appears poised to accelerate its internally developed embodied AI efforts by combining them with DeepSeek's models and training capabilities.

The competitive focus in humanoid robotics is increasingly shifting toward intelligence rather than locomotion alone. Beyond walking, running and finger dexterity, the key challenge is enabling robots to understand and execute human instructions autonomously. A task such as "Bring three red pencils from the blue basket on the desk and place them on the dining table" requires the integration of multimodal AI, reasoning, VLA models, world models and robot control systems.

Unitree aims to strengthen those capabilities through DeepSeek, while DeepSeek gains entry into a new category of AI models. DeepSeek's rise disrupted the dominance of high-cost U.S. AI models, leading to terms such as the "DeepSeek Moment" and "DeepSeek Shock." However, DeepSeek's existing systems are fundamentally large language models (LLMs). Expanding into robotics requires access to physical-world training data, which Unitree can provide.

DeepSeek has also been viewed as relatively weaker in multimodal integration. The partnership with Unitree could help strengthen those capabilities, as robotics models rely heavily on spatial understanding derived from camera-based perception before taking physical actions.

Meanwhile, Unitree is scheduled to begin IPO subscriptions on Aug. 10 on Shanghai's STAR Market before commencing trading. On Aug. 7, the company set its IPO price at 150.80 yuan per share, implying a valuation of approximately 61 billion yuan. Unitree plans to issue about 40.45 million new shares and raise roughly 6.1 billion yuan.

Naver said it will introduce a membership-exclusive dawn delivery service in October and begin generating revenue from its AI Factory project next year.

During its second-quarter 2026 earnings conference call on Aug. 7, the company said it plans to launch a dedicated dawn delivery service alongside a membership-only returns center that will provide faster returns processing. Since expanding free shipping and return benefits under its N Delivery membership program, customer purchase frequency has increased by about 29%, while the program's share of transactions has exceeded 70%.

Naver is also accelerating its AI infrastructure business. The company plans to begin operating its AI Factory project with Nvidia at 55 megawatts of capacity in the first half of 2027, when it expects the facility to start generating revenue. Capacity is targeted to expand to 100 megawatts by the end of 2027 and 200 megawatts in 2028. Naver is currently discussing the development of approximately $9 billion in computing infrastructure for the project with Brookfield.

The company noted that investment spending will remain elevated in the second half of the year due to continued deployment of Npay Connect and investments in computing assets such as graphics processing units (GPUs) and central processing units (CPUs). Naver said 2026 represents the peak period for growth-related investment and expects the pace of cost increases to moderate beginning next year.

The company reported second-quarter consolidated revenue of 3.39 trillion won and operating profit of 520.3 billion won. Revenue increased 16.2% from a year earlier, while operating profit declined 0.2%.

Revenue from the Naver Platform segment rose 12.3% year over year to 1.90 trillion won. Advertising revenue increased 7.5% to 1.45 trillion won, supported by expanded AI-driven advertising optimization. The company said AI accounted for more than 60% of incremental advertising revenue growth during the quarter.

Naver has also begun monetizing generative AI services. AI Briefing Ads, which were tested during the second quarter and officially launched at the end of July, delivered cost-per-click and click-through rates more than 30% higher than traditional search advertisements. Purchase conversion rates were more than three times higher. The company said it plans to expand the service as a new advertising inventory rather than a replacement for existing search advertising.

Service revenue, including commerce operations, increased 31.3% year over year to 455.0 billion won. Gross merchandise volume on Smart Store rose 15.5% during the quarter, while transaction volume on the Naver Plus Store app increased by more than 35%.

The company is also strengthening its logistics capabilities. Transaction volume through Smart Store's N Delivery service rose 76% year over year in June, and N Delivery accounted for more than 20% of total platform transactions. Naver plans to increase that share to 25% by the end of this year.

Naver posted double-digit revenue growth in the second quarter, but operating profit edged lower as spending on AI infrastructure and World Cup broadcasting rights weighed on earnings.

The company said on Aug. 7 that consolidated revenue reached 3.39 trillion won in the second quarter of 2026, up 16.2% from a year earlier. Operating profit declined 0.2% to 520.3 billion won.

According to Naver, the decline in operating profit reflected one-time costs related to the rollout of its offline integrated payment terminal, Npay Connect, broadcasting rights for the 2026 FIFA World Cup held from June 12 to July 20, intellectual property (IP) recognition expenses and investment in graphics processing unit (GPU)-based AI infrastructure.

Revenue growth was led by the Naver Platform segment, which includes advertising and commerce services. Segment revenue rose 12.3% year over year to 1.90 trillion won.

Advertising revenue increased 7.5% from a year earlier, supported by AI-driven content optimization and enhanced targeting capabilities. The company said AI contributed more than 60% of advertising revenue growth. Naver is also developing AI Briefing Ads, launched at the end of July, as a new revenue source powered by generative AI. The company said the product has delivered click-through conversion rates more than 30% higher than conventional search advertising and purchase conversion rates more than three times greater.

Service revenue, including commerce operations, rose 31.3% year over year, driven by growth in Naver Plus Store, membership services and N Delivery.

The financial platform business generated revenue of 470.7 billion won, up 16.0% from a year earlier, as the company continued expanding its payment ecosystem. Npay payment volume increased 21.0% to 25.2 trillion won, supported by growth in Smart Store transactions and expansion of external merchant networks.

Naver is also expanding Npay Connect as part of its push into AI-powered business platforms. The company plans to integrate online and offline data to strengthen its ecosystem and create new monetization opportunities.

Global business revenue rose 24.4% year over year to 1.02 trillion won. Consumer-to-consumer (C2C) operations were the main growth driver, with revenue increasing 74.9% from a year earlier, supported by higher transaction volume and revenue at Wallapop, Poshmark and Soda.

Content revenue increased 0.5% from a year earlier, while enterprise revenue rose 21.3%, supported by growth in business-to-business (B2B) sales related to AI and digital twin projects.

Naver said it is expanding AI infrastructure initiatives alongside the integration of AI across its existing services. The company expects revenue from its AI Factory project with Nvidia to begin in the first half of 2027.

LG Uplus said during its second-quarter 2026 earnings conference call that it plans to pursue a growth strategy centered on two pillars in the second half of the year: AI data centers (AIDC) and AI contact centers (AICC).

According to the company, revenue from its enterprise infrastructure division rose 8.6% year over year to 464.4 billion won in the second quarter. Within the segment, AIDC revenue increased 28.9% to 124.1 billion won, driven by growth in colocation services. The company said AIDC was the primary driver of growth in the enterprise infrastructure business.

LG Uplus is currently building a 200-megawatt (MW) AIDC campus in Paju, which it described as the largest facility of its kind in the Seoul metropolitan area. The company plans to open the first data center building in the first half of next year and said it has accelerated the construction schedule to meet rapidly growing demand for AIDC infrastructure.

The company also plans to secure additional power capacity through design-build-operate (DBO) projects while simultaneously expanding into regional locations. “Although it is difficult to precisely forecast GPU-based AI demand, we have secured a phased and scalable AIDC pipeline that can respond flexibly to changes in demand,” the company said.

During the conference call, Jung Young-hoon, head of Enterprise AI Business at LG Uplus, said demand in the AIDC market can be broadly divided between inference services concentrated in the Seoul metropolitan area and training and non-real-time inference workloads located in regional areas. He added that the company is investing a total of about 2 trillion won, including an additional 1.3 trillion won for the second phase of the Paju AIDC project.

Addressing questions about financing for AIDC construction, the company stressed that the projects are being funded without external capital raising.

Yeo Myung-hee, chief financial officer (CFO) of LG Uplus, said capital expenditures (CAPEX) related to AIDC will increase this year compared with last year, but will remain within the company’s EBITDA (Earnings Before Interest, Taxes, Depreciation, and Amortization) framework.

“We are improving capital efficiency and reducing pressure on cash flow by combining our own facilities with lighter models such as leasing and DBO projects,” Yeo said. “As a result, we plan to pursue our medium- to long-term AIDC targets without separate external financing.” She added that investment plans could change depending on market conditions and that the company would communicate any changes promptly.

For its AICC business, LG Uplus said it will continue enhancing its solutions by incorporating operational expertise and customer pain points gained as an actual user running customer service centers with more than 4,000 agents.

During the first half of the year, the company focused on deployment-based projects in the financial sector and secured reference customers. In the second half, it plans to expand its product lineup with large language model (LLM)-based offerings in addition to existing products such as Consultation Advisor and AutoQA. The company said it aims to accelerate tangible results from AI-driven new businesses by leveraging the competitiveness of its internalized AICC solutions.

Revenue from the solutions business, which includes AICC and smart mobility services, rose 6.8% year over year to 134.6 billion won in the second quarter, supported by growth in messaging relay services.

The conference call also included questions regarding profitability differences between conventional internet data centers (IDC) and AIDC, as well as potential business and role overlap between LG Uplus and LG CNS within the LG Group’s AI strategy.

The company said profitability at newly built AIDCs, including the Paju facility, is expected to exceed that of traditional IDC operations. Data center revenue is generally divided into space rental fees and electricity charges. Space rental fees command higher pricing because investments in liquid cooling and power infrastructure are required to support AI servers and ensure operational stability.

LG Uplus also noted that demand continues to significantly exceed supply, pushing space rental unit pricing higher. While electricity fees are typically charged on a metered basis according to usage, the higher utilization rates of AI servers are also increasing overall electricity-related revenue, the company said.

Regarding potential overlap in business and roles with LG CNS within the group, the company avoided direct comparisons but said both firms possess capabilities in the design, construction and operation of AIDCs, while their business models differ according to their respective strengths and customer bases.

The company said LG Group is pursuing a “One LG” strategy to advance AI infrastructure and create new value. “The group will strengthen competitiveness in AI infrastructure by combining cooling, power operations and network capabilities across affiliates, while enhancing the value chain through integration with AI technologies such as EXAONE from LG AI Research,” it said.

Within that framework, LG Uplus emphasized that it serves as a core operator handling AI infrastructure operations. As a provider capable of delivering both data center and telecommunications network services, the company said it is expanding its maximum data center capacity through both self-owned facilities and external DBO projects, which it began pursuing last year.

“Based on our AIDC infrastructure in key metropolitan locations, network capabilities and data center operating expertise, we plan to continue expanding AI infrastructure to meet growing demand,” LG Uplus said. “Through this approach, we will maximize synergies across the group, manage operational risks through demand-driven investment and improve investment efficiency.”

OpsNow, an AI-powered multi-cloud management platform provider, said on Aug. 6 that it has simultaneously obtained ISO/IEC 27001:2022 certification for information security management systems and ISO/IEC 27701:2025 certification for privacy information management systems. The certifications cover the development, operation and delivery of its cloud management platform.

ISO/IEC 27001:2022 is a globally recognized information security standard awarded after an assessment of 93 control measures across four areas: organizational, human, physical and technological security. ISO/IEC 27701:2025, meanwhile, was revised in October 2025 and transitioned from an extension of ISO/IEC 27001 into an independent management system standard.

Organizations certified under the previous 2019 version are required to transition to the updated standard by October 2028. OpsNow said it received certification under the latest 2025 version, validating its management framework in its role as a personally identifiable information (PII) controller. The certifications are valid for three years.

With the new certifications, OpsNow said an independent external audit has verified that its management systems for platform development and operations, as well as its privacy governance framework as a PII controller, comply with international standards.

OpsNow's multi-cloud management platform provides services ranging from cloud infrastructure resource management and multi-cloud cost optimization to cloud security posture management (CSPM) and AI-based operational automation. The company said security is a core competitive factor because the platform directly handles customers' critical infrastructure, cost and configuration data.

OpsNow expects the certifications to accelerate its expansion into global markets. The company said the internationally recognized management frameworks will help satisfy due diligence requirements commonly requested by customers in the United States, Europe and Asia, strengthening its ability to win overseas business. It also expects stronger momentum in the enterprise market, particularly among large corporations, financial institutions and public-sector organizations where security regulations and compliance requirements are stringent.

Trimble, a global provider of 3D building information modeling (BIM) solutions, said it has successfully deployed its Trimble Connect and Trimble Connect Dashboard platforms at Kolon Global, establishing a BIM-based digital integrated management system for steel frame construction that enables real-time monitoring of fabrication, shipment, delivery and installation progress.

Kolon Global said it has been diversifying its business portfolio beyond housing projects into general building construction and high-tech facilities, while expanding its BIM processes from reinforced concrete (RC) structures to steel and precast concrete (PC) structures. As part of that transition, the company identified the need to reduce data discrepancies and communication issues associated with 2D drawing- and spreadsheet-based management systems, while shortening the performance aggregation process—which previously took more than a week—to quickly identify schedule delays and project risks.

Through Trimble Connect and Trimble Connect Dashboard, Kolon Global said it can now manage the entire steel construction process, from fabrication to installation, through a unified real-time digital platform.

When partner companies upload shop models created with Tekla software to Trimble Connect, the status of each steel component is displayed through color-coded indicators on a 3D model. By linking QR codes assigned to individual components and shipping invoices, fabrication, shipment, delivery and installation data are updated in real time, enabling construction sites, headquarters and subcontractors to track project progress using the same dataset.

Following implementation, the company said performance aggregation processes that previously required more than a week have been replaced by a real-time monitoring system. The platform also provides visibility into material deliveries, installable inventory and actual performance against plans, allowing delays to be identified early and enabling faster corrective actions such as adjusting production volumes or revising installation schedules.

In addition, quantity information from 3D shop models can be compared and verified against subcontractor progress payment claims, helping prevent overbilling and enabling more accurate settlements through component-level verification. The company also said the system has improved decision-making speed by allowing project owners and supervisors to review construction progress using the same data standards without requiring additional reporting work.

Kolon Global plans to expand the system beyond steel construction to precast concrete processes and eventually deploy a standardized digital construction management framework across all of its steel and PC project sites.

ADT Caps, the physical security brand of SK shieldus, said on Aug. 6 that it has launched Caps Store Solution, a new integrated service designed to manage both store operations and security through a single application.

Caps Store Solution enables real-time management of security, access control, attendance, sales and connected devices through Caps ON, the company's unified management platform.

The service can be customized for a wide range of retail environments, including hybrid stores, unmanned stores, small single-operator shops and franchise locations. Users can select only the functions they need, such as access authentication terminals, kiosks and doorbells, and configure the system accordingly.

Selected functions can be managed through the Caps ON mobile application. Based on sales data collected from payment devices such as kiosks, operators can monitor sales performance by time period and product category. The platform also analyzes operational data to support more efficient store management and data-driven decision-making.

When integrated with ADT Caps' security response service, the solution allows businesses to handle routine store operations and emergency response through a single management framework.

RaonSecure said on Aug. 6 that it has been selected as a participating company for the 2026 Blockchain Specialized University (Graduate School) Support Program, an initiative led by South Korea’s Ministry of Science and ICT and the Korea Internet & Security Agency (KISA).

The program was established to cultivate industry-ready blockchain professionals through cooperation between universities and the private sector. It aims to narrow the gap between education and industry demand by integrating blockchain coursework, hands-on training and problem-solving projects.

RaonSecure will operate the “University Hub,” providing a common blockchain technology infrastructure to participating institutions including Seoul Women’s University, Konyang University and Hansei University. The company will build a shared training environment where students can learn blockchain technologies in conditions that closely resemble real-world industry settings.

RaonMeta, a subsidiary of RaonSecure, will provide extended reality (XR)-based learning environments through dedicated university sections of Metademy, its artificial intelligence (AI) and virtual convergence training platform. The system will allow students to experience step-by-step development processes in immersive educational settings.

In addition, RaonSecure will issue digital credentials through its OmniOne Badge platform, enabling learning achievements to be recorded on blockchain infrastructure. Students who meet specified requirements will be eligible to receive a professional digital identity based on decentralized identity (DID) technology through OmniOne Digital ID, the company’s blockchain-based integrated identity and credential verification platform.