After the internal testing of WeChat's personal version AI Agent "Xiaowei" was launched, Enterprise WeChat also officially started the internal testing of its AI Agent with the code name "Dayuan" today. This product is positioned as an AI assistant "integrated into the workflow of Enterprise WeChat," aiming to automatically understand user requests and provide responses based on existing work data within Enterprise WeChat, such as group chats, documents, meetings, emails, and schedules.

Swipe left to activate, use AI like chatting

In terms of interaction, "Dayuan" is deeply integrated into the daily operations of Enterprise WeChat. On mobile devices, users can simply swipe left on the interface to activate this feature, and the system can intelligently identify the current screen and the question being asked. When there are too many group chat messages, swiping left and asking "What are they discussing in the group?" will allow the AI to automatically summarize. When receiving a complex data report, swiping left again allows the AI to extract key conclusions. On mobile devices, "Dayuan" supports activation from multiple entry points, such as the message page and chat windows, without needing to open a separate AI tool, making it more like a naturally embedded product form within the workflow.

Not just an internal assistant, but also help frontline employees "manage clients"

The inherent connection between Enterprise WeChat and WeChat means that "Dayuan" will not only serve internal collaboration in the future, but also further enter customer management scenarios. According to feedback from users participating in the internal test, the currently gray-scale tested "Service Summary" feature can automatically extract customer needs, deal intentions, and obstacles during employee-customer communication, and periodically push suggestions for key customers to follow up on. Customer groups and customer information can be automatically stored in AI-powered tables, forming a unified management center. The AI in these smart tables not only summarizes follow-up status, but also generates data analysis dashboards, breaking down customer intent, conversion funnels, and service quality.

Previously, the massive communication records between sales, customer service, and customers relied heavily on manual checks for customer intent, follow-up progress, and key points of past communication. The introduction of the AI Agent can understand and organize these customer conversation data, transforming originally scattered and unstructured communication content into reusable customer profiles, follow-up summaries, and business insights, which is particularly critical for enterprises that rely heavily on Enterprise WeChat for private domain operations.