May-I Revolutionizes Data Decision-Making with Conversational AI 'Mesh Insight'

Computer vision AI startup May.i has brought a groundbreaking change to its visitor data analysis solution 'mAsh'. By newly adding the conversational AI agent 'mAsh Insights', it has elevated user experience and operational efficiency to a new level. The existing mAsh solution analyzed in-store CCTV footage using deep learning technology, tracking visitor movements to precisely measure key metrics like visit-to-purchase conversion rates and suggest improvement strategies. Now, mAsh Insights, which combines a powerful large language model (LLM), helps businesses access data much more easily and make strategic decisions. Users simply need to click the 'AI Analysis Function' button in the web dashboard 'mAshboard,' select the desired metric, and input their question. As if a competent data analyst were right beside them, mAsh Insights immediately provides accurate and highly reliable answers to questions. Security is also thorough. An enterprise-grade system based on AWS's 'Amazon Bedrock' and robust encryption technology minimize information errors. It preprocesses visitor data based on user questions, securely protects sensitive information, and then presents the most accurate analysis with its proprietary inference algorithm. Based on a deep understanding of offline stores and natural language processing technology, this smart solution provides real-time information and proposes practical strategies directly applicable to operations such as marketing and store management. Furthermore, it supports store operation optimization and performance maximization through in-depth analysis that examines causal relationships with external factors like weather, events, and commercial areas, and predicts business indicators. May.i plans to continue strengthening cooperation with its clients and continuously developing its inference algorithms. Additionally, it intends to introduce an 'automatic report generation function' that automates the collection and analysis of visitor data, thereby significantly reducing the burden of data analysis and report writing, and further enhancing operational efficiency.