EVA v2.4.0: Taking Detection Monitoring Efficiency to the Next Level​

The EVA v2.4.0 release reflects the requirements raised in real operational environments, significantly improving monitoring efficiency and user experience. This update focuses on Alarm Priority Sorting, Device Favorites, and Expanded Language Support, delivering convenience that can be felt immediately in monitoring operations.

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Alarm Priority Sorting – Never Miss Real-Time Responses Among Numerous Devices​

In a monitoring environment with numerous connected devices, the most important thing is immediate identification and response to alarm-triggered points. When a detection alarm occurs, EVA automatically moves the corresponding device to the top of the list, allowing you to quickly and easily identify the alarm-triggered device even in a complex list. This feature is designed to display the latest events at the top in order, even when multiple alarms occur simultaneously, so you can see the most critical screen at a glance without scrolling or searching. As a result, monitoring efficiency and response speed are greatly improved, and when combined with the Favorites feature, you can prioritize monitoring of key devices where alarms occur.

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Device Favorites – Focused Monitoring of Key Points by Operator​

The more cameras you monitor, the more important it is to quickly check critical points. With this update, EVA allows users to register key devices they manage as favorites and filter them for instant access. This feature is especially useful in environments where device responsibility varies by operator. Each operator can manage their critical devices as a favorites group to ensure no important point is missed and maintain focused monitoring. Grouping priority monitoring cameras such as entrances, high-value equipment storage areas, and safety management zones will further enhance monitoring efficiency.

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Expanded Language Support – EVA Accessible to Everyone​

EVA now supports both Korean and English. You can select your preferred language in the settings menu, and language changes can only be made by accounts with administrator or manager privileges. This update makes EVA easy to use even for users unfamiliar with AI by providing all screens and functions in Korean and simplifying technical terms. In addition, detection analysis results can be provided in the desired language to minimize communication errors, enabling quick adaptation for new users and consistent information sharing across teams.

We held strategic discussions with Ringnet CEO Lee Jeong-min regarding the expansion of the EVA business.

As the domestic distributor of Cisco Meraki, Ringnet is a specialized partner with powerful network/security infrastructure and on-site implementation capabilities. Through collaboration with LG Electronics, Ringnet will play a crucial role in expanding EVA's Physical AI technology across various industries, including manufacturing, logistics, and the public sector.

During this meeting, we discussed in-depth strategies for nationwide and global expansion, building on the success of the "Meraki CCTV + EVA" integration PoC (Proof of Concept) verified at the LG Electronics Pyeongtaek Digital Park. Based on the success factors of the Pyeongtaek case, we explored ways to seamlessly integrate EVA into the Meraki ecosystem, making it easier for domestic manufacturing companies to adopt the solution and establishing a foundation for long-term global market expansion.

Regarding the direction of the partnership, we agreed to promote mutual growth through various business models, such as proposing an integrated package of "EVA + Meraki CCTV + Action Trigger" sensors, as well as standalone EVA sales structures. Ringnet plans to identify key targets within its existing customer base in manufacturing, distribution, logistics, and the public sector through consultation with its sales force, which will further accelerate EVA's market penetration.

Notably, at the Manufacturing Summit hosted by Cisco Korea on January 29, EVA will be featured and demonstrated as the main solution at the Ringnet booth. Moving beyond a simple CCTV exhibition, we are co-developing real-time demo scenarios designed to capture customer interest. These collaborative efforts are opening new possibilities for EVA to lead innovation in safety, security, and operations at domestic manufacturing sites by combining with Meraki's global cloud infrastructure.

We look forward to the exciting developments ahead.

The era of "Actionable AI"—AI that moves beyond theoretical potential to solve real-world industrial challenges—has arrived. We are officially kicking off a strategic collaboration to fundamentally transform industrial sites by combining the deep Foundation AI research capabilities of our AI researchers with mellerikat’s innovative Physical AI platform, EVA.

While previous AI focused on providing general answers, our core mission is "Vertical AI."

• Researcher-led Vertical Foundation Models: Our AI researchers develop Foundation models equipped with specialized knowledge and reasoning capabilities optimized for specific industrial sectors.
• Commercializing Industry-Specific Services with EVA: These Vertical models are immediately integrated into mellerikat’s EVA. Through EVA’s natural language-based scenario settings and real-time field control technology, they are transformed into AI applications that work instantly on-site without the need for complex coding.

A Paradigm Shift in Industrial Safety for Construction and Manufacturing​

Our primary focus is "Industrial Safety," a domain where the highest levels of precision and reliability are mandatory.

• Safety-Specific Models: We are building dedicated models that possess a deep understanding of the unique risk factors found in construction and manufacturing environments.
• Intelligent Monitoring Solutions: By combining EVA’s vision capabilities—which "understand" rather than just "see"—we plan to supply next-generation safety solutions to major manufacturing and construction firms. These solutions go beyond simple intrusion detection to proactively predict and respond to risky worker behavior.

Leap forward as a Key Player in the EXAONE Ecosystem​

This collaboration aligns with the LG EXAONE Alliance, South Korea’s premier hyperscale AI ecosystem.

Core Agentic AI Platform: Within the EXAONE ecosystem, which currently features 23 leading partners, EVA serves as the core Agentic AI platform connecting the physical world with AI. Global GTM (Go-To-Market): Leveraging the powerful synergy of the EXAONE ecosystem, we will accelerate our global market entry and secure strong market competitiveness alongside partners from various domains.

Together with our AI researchers, we are standing at the center of innovation—a journey where technology crosses the threshold of the lab to prove its value in the most demanding industrial fields of our lives.

Campus: Beyond Safety to Intelligence – Postech Living Lab Project with EVA​

A university campus is an ocean of data. Thousands of people move, live, and interact every day. Until now, cameras in this space existed only for “security” and “surveillance.” Countless recorded video data created no value and were discarded over time.

We asked a question: "Instead of simply discarding this vast data, can we use it as an 'asset' to make the campus smarter?"

From this question, the Postech Living Lab project based on EVA (Evolved Vision Agent) began.

This document provides a comprehensive overview of the detailed configuration and technical vision of EVA.

[Overview]​

EVA serves as 'The Brain of Physical AI,' powered by a Multi-Foundation Model that integrates Vision Models (VM), Vision-Language Models (VLM) and Large Language Models (LLM). It goes beyond simple object detection; by leveraging VLM, EVA understands complex visual contexts and situational nuances, acting as an intelligent agent that makes autonomous decisions aligned with user intent.

[Key Highlights]​

• Multi-Foundation Model Architecture: Foundation models for vision (VM), vision-language (VLM), and large language (LLM) are organically linked to analyze scenes from multiple perspectives and make common-sense judgments.
• Interactive Scenario Setting: Define detection scenarios using natural language without complex coding. Users can refine AI performance in real-time through conversational feedback.
• Human-in-the-Loop: User feedback is immediately incorporated into the learning process, allowing the vision agent to become increasingly optimized for specific environments over time.
• Closing the Loop (Action): Beyond situational awareness, EVA completes the loop by executing physical actions, such as robot control and facility management, to resolve issues.

[Resources]​

For more details, please refer to the document below.

📂 EVA_Intro_20251211.pdf

EVA v2.3.0: Three Innovations to Make On-Site Operations Smarter and More Precise​

The EVA v2.3.0 release is not just about adding new features—it’s an update designed to eliminate inefficiencies in large-scale camera operations, improve detection accuracy, and dramatically enhance the user experience. EVA is now smarter, more intuitive, and more powerful than ever.

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Say Goodbye to Repetitive Tasks! Common & Custom Detection Scenarios​

One of the biggest challenges in managing large-scale camera operations is the inefficiency of registering the same detection scenario across dozens or even hundreds of cameras. For example, if you manage 100 cameras, you previously had to register the same scenario 100 times—a time-consuming and labor-intensive process.

EVA v2.3.0 solves this problem by introducing the Common Scenario feature. Now, administrators only need to define a Common Scenario once in the EVA settings menu. Connected cameras can automatically apply this scenario, and if needed, you can add Custom Scenarios for individual cameras. Furthermore, EVA allows both Common and Custom Scenarios to be applied simultaneously, greatly improving operational flexibility.

What benefits does this bring to EVA users?​

• Significantly reduces registration time and repetitive tasks in large-scale operations.
• Updates to Common Scenarios are automatically reflected across all cameras, maximizing management efficiency.
• Administrators can focus on strategic operations and safety enhancements instead of repetitive work.

I had an insightful session with Raymond, VP and APAC Sales Lead at Cisco, exploring strategic collaboration opportunities between Mellerikat EVA and Cisco’s cloud-managed Meraki camera platform.

The synergy between Meraki’s highly scalable, cloud-native video infrastructure and EVA’s lightweight yet high-precision AI vision engine offers significant potential across multiple industries. By combining Meraki’s centralized management and secure architecture with EVA’s advanced scenario detection capabilities, organizations can elevate an existing camera network into a powerful real-time intelligence platform—without additional hardware deployment.

During our discussion, we aligned on establishing an EVA demo environment at Cisco’s headquarters and initiating joint PoCs leveraging video data from Meraki cameras installed in public sectors such as schools and airports. These efforts aim to validate various safety, operational, and risk-detection use cases that can unlock new service models.

This collaboration represents a compelling opportunity to merge cloud-first infrastructure with cutting-edge AI. Exciting developments lie ahead.

We recently held a collaborative session at KOCOM’s Magok headquarters to explore deeper partnership opportunities. During the meeting, both teams engaged in an in-depth discussion on KOCOM’s business model and the technical strengths of Mellerikat EVA, examining concrete pathways for applying AI-driven capabilities across real-world use cases.

KOCOM expressed strong interest in EVA’s economic efficiency and scalability, and both sides agreed to pursue a joint Proof of Concept (PoC) along with continued discussions to refine potential business models.

The session also provided valuable insight into how advanced AI technology can drive innovation in smart buildings and home IoT solutions, highlighting promising opportunities within the residential market.

Building on this momentum, both companies will continue strengthening their collaboration to deliver next-generation AI-powered smart living experiences. More exciting developments lie ahead.

EVA Proposes AI-powered Intelligent Safety CCTV Innovation at LG Electronics Enterprise Safety & Health Leaders Workshop​

📍 November 14, 2025 (Fri), LG Digital Park Learning Center

At the "2025 Second Half Enterprise Safety & Health Leaders Workshop" held at the LG Digital Park Learning Center, we had the meaningful opportunity to introduce the EVA solution. The one-hour session focused on "AI-based Intelligent Safety CCTV" and presented EVA’s innovative safety management capabilities along with a roadmap for enterprise-wide deployment.

During the workshop, Mellerikat EVA highlighted ease of operation and cost efficiency as its core values. Leveraging multimodal LLM-based technology, EVA demonstrated real-time detection of worker safety status through simultaneous analysis of video and text data, coupled with instant alert functionality. This approach represents a key strength that sets EVA apart from conventional high-cost AI systems.

Following the session, an active Q&A took place, during which participants reaffirmed EVA’s potential to deliver tangible value in the safety and health domain across the following dimensions:

• Ease of Operations: Easy deployment and operation at worksites
• Cost Efficiency: Remarkable economic advantage over existing solutions
• Scalability: Continuous expansion through ongoing updates to both the solution and foundation models

During the workshop, EVA was proposed as a company-wide safety management solution. Through its adoption, we envision the establishment of an intelligent safety management system not only at LG Digital Park but across all LG workplaces, ensuring enhanced accident prevention and operational efficiency.

EVA Showcases Innovation with Multi-Modal LLM-Based AI Services at Cisco Live 2025​

Cisco Live 2025, June 8-12, 2025, San Diego

Mellerikat participated in Cisco Live 2025, seizing a valuable opportunity to present its innovative AI service, Mellerikat EVA, powered by Multi-Modal Large Language Models (LLMs), to global customers and partners. At this premier event focused on networking, security, and AI technologies, Mellerikat showcased a demo featuring a unique architecture that implements cost-efficient AI solutions, earning enthusiastic responses from attendees. As the first major event following Cisco’s acquisition of Splunk, Cisco Live 2025 highlighted the integrated future of AI and data analytics. Mellerikat unveiled a Multi-Modal LLM-based solution combining Mellerikat EVA, Cisco Meraki Camera, and Splunk Instance through its demo booth, demonstrating practical AI applications in industrial settings. Notably, our innovative architecture, which significantly reduces the operational costs of Multi-Modal LLMs, left a lasting impression on attendees.