Exhibitors

BPA is a next-generation AI Agent-driven business process automation platform that integrates cutting-edge technologies such as large language models (LLM), AI generation, OCR, and process mining. Based on the "Human-in-the-Loop, human-machine collaboration" concept, it assists enterprises in achieving digital business transformation. It shifts traditional human-centered business operations to an AI-agent-driven business process automation model, upgrading roles and reshaping the human-machine collaboration paradigm. Employees transition from being operators to process monitors, focusing on high-value-added business activities and supervising and training AI digital employees instead of engaging in repetitive manual tasks.

Integrates multi-source data such as natural geography, human activities, and IoT to build a unified spatio-temporal data management system. It offers functions like data fusion, intelligent analysis, and visualization, supporting applications in government services, logistics, emergency response, and more. By deeply mining spatio-temporal data and empowering industries, it optimizes resource allocation, enhances decision-making efficiency, and provides a comprehensive, intelligent solution for the low-altitude economy sector.

Leveraging large language model technology, combined with expert systems and industry knowledge bases, AIGC assists financial institutions in internalizing external regulations, intelligent interpretation, automated report generation, and compliance process checks in the field of intelligent risk control.

The MLOps platform offers a one-stop solution for AI model training, deployment, data annotation, and API integration, assisting small and medium-sized enterprises in rapidly achieving AI transformation.

Introducing an audit knowledge base to improve audit management efficiency; adopting a knowledge-driven model for intelligent audit operations; broadening audit perspectives to strengthen risk identification capabilities; promoting knowledge sharing to build a collaborative supervision-audit ecosystem.

An AI-based OCR CV intelligent quality inspection one-stop solution, suitable for various industrial scenarios, offering high accuracy and customizable intelligent quality inspection options.

Dedicated to building a digital and intelligent low-carbon urban complex, we aim to construct a panoramic carbon emission monitoring "brain." Through IoT perception, data empowerment, smart decision-making, and trustworthy connections, we achieve comprehensive digital emission reduction from the government, parks/buildings, enterprises/institutions to the public. This deeply integrates low-carbon elements into the city's pulse, promoting efficient implementation of carbon neutrality policies and carbon reduction strategies, thereby assisting cities in achieving their carbon neutrality goals.

<table border="0" cellpadding="0" cellspacing="0" style="border-collapse: collapse;width:322pt;" width="429"><tbody><tr height="144" style="mso-height-source:userset;height:108.0pt;"><td height="144" style="height:108.0pt;width:322pt;" width="429">Leverages digital twin technology to create a 3D warehouse environment, integrating warehouse management systems, automation equipment, and AI technology for comprehensive digital management. It covers core functions such as inventory tracking, order processing, and intelligent scheduling, optimizing warehouse processes, reducing manual intervention, and enhancing operational efficiency and accuracy. Through visual management, smart decision-making, and automated processes, it helps customers manage inventory scientifically, reduce operational costs, improve order fulfillment, and build an efficient, eco-friendly, and unmanned warehouse system. </td></tr></tbody></table>

We are dedicated to creating an intelligent and efficient park environment by integrating advanced technology with park management, enhancing quality of life and corporate competitiveness. Through smart facility management, data-driven decision-making, intelligent security systems, and convenient smart services, we bring comprehensive changes to the park. Join us in shaping a smarter, more convenient future for cities together!

Utilize generative AI technology to optimize the government's project application and review process:Accurately detect the similarity of application materials to ensure their authenticity and compliance.Optimize the expert recommendation system with AI to guarantee fairness and impartiality in the review.Provide policy analysis and push services to help enterprises quickly understand policy content.This can effectively improve the efficiency of government project application and review, and contribute to the optimization of government resources and the development of key projects.

By constructing a quality knowledge graph based on work units and a Retrieval Augmented Generation (RAG) system based on Large Language Models (LLM), the efficiency and accuracy of quality information processing in the equipment manufacturing process can be improved, enabling the effective extraction and reuse of technical data and materials.

Focusing on the application scenarios of domain knowledge within enterprises, leveraging technologies such as Large Language Models (LLM), Retrieval Augmented Generation (RAG), Knowledge Graph, and AI Agent, we aim to enhance the utilization and inheritance efficiency of business and management knowledge in the enterprise's private domain, activate the value of the enterprise’s private - domain data assets, and assist the enterprise in improving quality and increasing efficiency.

Process mining is a product developed for creating a Digital Twin of an Organization (DTO). It combines technologies such as data science, process management, and artificial intelligence to enable the visual monitoring of business processes. By understanding, improving, and optimizing business processes, it enhances workflow efficiency, effectiveness, and productivity, maximizing business outcomes. It can identify business bottlenecks and use analytical techniques to find the causes of inefficiencies and optimize resource allocation, thereby achieving task automation.

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