What is EVA?
EVA is an intelligent solution that transforms ordinary cameras into smart AI cameras. By seamlessly integrating machine learning (ML), large language models (LLM), and vision language models (VLM), EVA enables users to easily and quickly build desired vision AI services without complex development processes. Since it can be configured and controlled through natural language conversations, field managers can intuitively utilize EVA.
For more details, visit the EVA introduction page.
Key Features
EVA’s greatest strength is simplifying complex AI technology for everyone. Users can set detection rules with simple natural language commands like “Detect people in this area,” and EVA automatically configures the appropriate models and logic. Additionally, the AI model self-optimizes based on the field environment, allowing immediate application without separate data collection or labeling.
Errors during detection are continuously improved through user feedback, enabling EVA to increasingly reflect the specific needs of the site. This allows EVA to go beyond simple object recognition, performing contextual analysis and situational understanding.
EVA can be customized for various industries, such as safety management, quality inspection, anomaly detection, and security monitoring. Its Super Agent and Sub Agent architecture flexibly handles complex requests.
User Scenario
EVA’s usage process is highly intuitive. Managers only need to register the address and information of a network camera, and EVA automatically converts it into a smart AI camera. Afterward, users can make requests through a conversational interface, such as “Detect people not wearing safety helmets” or “Notify me of loitering behavior in this area.”
EVA sequentially leverages ML, VLM, and LLM to detect objects, understand situations, and provide meaningful judgments. If incorrect results occur, user feedback helps EVA learn to deliver more accurate judgments in the future.
Through this process, EVA becomes increasingly optimized for the site’s context over time, allowing operators to seamlessly introduce complex AI-based vision services without requiring specialized expertise.