Break through the limitations of a single product, support cross-assessment of multiple insurance types such as medical insurance, critical illness insurance, and life insurance. Conduct comprehensive parameter comparisons from coverage scope, compensation ratio to value-added services, visually present advantages and disadvantages, and assist users in making rational trade-offs and choices in the complex market.

Directly connect to the official data and service channels of major insurance companies, provide authoritative company solvency, service rating, and special policy consultation. Answer professional questions such as insurance application procedures, policy maintenance changes, and claim disputes, act as a transparent bridge between users and insurance companies, ensure worry-free services.

Based on users' age, health, budget, and family structure, precisely match thousands of products on the market. Not only recommend insurance types, but also provide detailed comparisons of specific clause responsibilities and rates, eliminate redundant coverage, and offer "one-size-fits-all" customized optimal insurance purchase plans.

Break down complex insurance terms in simple and understandable language. Through scenario-based cases, popularize basic knowledge such as underwriting, claims settlement, and exemption clauses. Help users establish a clear insurance cognition framework, eliminate information asymmetry, and enable beginners to easily understand insurance policies and purchase insurance clearly.

A leading insurance brokerage company has collaborated with Chuangzhi AI to implement the Xiaoyizhi Insurance AWS cloud deployment project, aiming to address the issues of low efficiency in insurance business consultation, insufficient accuracy of product recommendations, and difficulties in overall operation and maintenance management. The project has created a full-scenario intelligent question-answering assistant for insurance professionals, brokers, and decision-makers, providing comprehensive services including insurance general knowledge answers, precise product recommendations, and operational data analysis.

The project is built based on the AWS cloud ecosystem, with an accuracy rate of product recommendations exceeding 90%. It uses Amazon S3 to store insurance terms and product documents, Amazon RDS to manage business data, and VPC private networks to build a security system. CloudWatch is utilized to monitor the entire chain of model operation and service invocation, and the LLMOps system is used to manage the entire lifecycle of the model.

After the project was implemented, the efficiency of insurance business consultation for the enterprise increased by 200%, the rate of customer service calls to human agents decreased significantly, the sales ability of brokers improved markedly, and operational data analysis was used to inform product strategies, making it a typical cloud deployment practice of AI enabling the entire process of insurance business in the insurance industry.