**源雀 SCRM** is a private-domain digital and intelligent marketing solution based on WeCom, with 100% open source code.

Based on WeCom · Out of the box · Free customization · Private deployment

## Project introduction

As private-domain operations deepen and business competition becomes more differentiated, SCRM tool selection faces pain points such as serious product homogenization, lack of flexible customization, limited SaaS extensibility, and data security, privacy and compliance risks.

**源雀 SCRM** uses a 100% source-open delivery strategy to connect the integrated chain of **operations, marketing and service**, building a new marketing model from all-domain prospect acquisition to enterprise private-domain operations, with the goals of **out-of-the-box use, free customization, private deployment and continuous service**.

## System architecture

源雀 SCRM is built around the full chain of **prospecting → management → operations → marketing → service → analysis** for one-stop private-domain digital marketing.

- **Prospecting:** all-domain customer acquisition scenarios to quickly build a private-domain customer pool.

- **Management:** customer and customer-group profiles for refined management.

- **Operations:** automated operation strategies based on refined profiles.

- **Marketing:** strategy audiences and full-journey precise marketing.

- **Service:** WeChat intelligent customer service, content center, conversation archiving and digital employees.

- **Analysis:** private-domain full-chain data analysis to optimize marketing strategies.

## Open-source edition features

The open-source edition includes employee smart live codes, acquisition external links, smart group codes, customer public pool, complaint management, mass marketing, customer lists, employee lists, customer group lists, customer tags, group tags, content/material management, customer service scheduling, operation logs, group robots, file security and screenshot security.

AI features include an AI intelligent assistant, AI customer service, RAG-based knowledge-base management, AI conversation summaries, customer and group conversation analysis, AI violation pre-review, intent customer identification, hotword analysis and AI tag libraries.

## Technology stack and licensing

Backend: Spring Boot, JPA, MyBatis-Plus and MySQL. Frontend: Vue 3, Vite, Pinia and Element Plus. AI: LangChain4j, large models such as Zhipu AI, and Milvus vector database.

The project is released under the Apache 2.0 license and may be secondarily developed and used commercially while retaining the relevant logo and product-name information. It connects to the official WeCom APIs for compliance. Before secondary development, verify the WeCom application and callback configuration. The open-source edition does not provide a demo; the code is fully open and can be deployed independently.