Open-source CRM for sales teams built on the Frappe framework, with unlimited users, kanban pipelines and call and WhatsApp integrations.
1Panel-dev/CordysCRM
Open-source AI CRM system with private deployment, built-in BI via DataEase, and a CRM Skills interface for AI assistants.
Open-source alternative to:Salesforce
- Stars
- 2,804
- Forks
- 579
- Open issues
- 49
- Last commit
- 10 hours ago
What is it?
Cordys CRM is a customer relationship management system from FIT2CLOUD, designed for self-hosted deployment so that company sales and customer data stays under the organization's control. It covers opportunity management with list and detail views, role-based access control, and modules for quotes, contracts, orders, invoices and payment collection, along with an approval workflow.
The system integrates the DataEase analytics engine for visualizing sales data and self-service exploration. It also exposes an open API and a CRM Skills interface so AI assistants such as OpenClaw and WorkBuddy can work with sales records across the pipeline, from lead screening to deal analysis. The project is deployed with Docker, and its stack is Spring Boot on the backend with Vue.js, Naive UI and Vant UI on the frontend, backed by MySQL and Redis.
Key features
- 01Opportunity management with list and detail views
- 02Role-based access control and modular configuration
- 03Quote, contract, order, invoice and payment collection modules
- 04Built-in sales data visualization via DataEase
- 05Open API and CRM Skills interface for AI assistant integration
- 06Docker-based private deployment
Use cases
- Running a sales CRM on your own servers to keep customer data in-house
- Adding AI assistants to sales workflows such as lead qualification and deal analysis
- Building sales dashboards on top of CRM data with DataEase
- Customizing a CRM through its open API for internal business processes
Quick start
- 1
Prepare a Linux server with Docker installed
- 2
Run the Docker container
docker run -d --name cordys-crm --restart unless-stopped -p 8081:8081 -p 8082:8082 -v ~/cordys:/opt/cordys 1panel/cordys-crm - 3
Open http://<your server IP>:8081/ in a browser and log in as admin with the default password CordysCRM
Things to know
- Uses the FIT2CLOUD Open Source License, a custom license based on GPLv3 with extra restrictions, such as not replacing or modifying the logo and copyright.
- Default admin credentials are published in the README, so change them after installing.
Topics
FAQ
- What is CordysCRM?
- Open-source AI CRM system with private deployment, built-in BI via DataEase, and a CRM Skills interface for AI assistants. Cordys CRM is a customer relationship management system from FIT2CLOUD, designed for self-hosted deployment so that company sales and customer data stays under the organization's control. It covers opportunity management with list and detail views, role-based access control, and modules for quotes, contracts, orders, invoices and payment collection, along with an approval workflow.
- Is CordysCRM free to use? What license does it have?
- CordysCRM is open source under the Other license. Check the license terms before using it in commercial products.
- Is CordysCRM still maintained?
- Actively maintained. The last commit to CordysCRM was on Oct 21, 2026.
- What can I use CordysCRM for?
- Running a sales CRM on your own servers to keep customer data in-house Adding AI assistants to sales workflows such as lead qualification and deal analysis Building sales dashboards on top of CRM data with DataEase Customizing a CRM through its open API for internal business processes
- How do I install CordysCRM?
- Prepare a Linux server with Docker installed Run the Docker container: docker run -d --name cordys-crm --restart unless-stopped -p 8081:8081 -p 8082:8082 -v ~/cordys:/opt/cordys 1panel/cordys-crm Open http://<your server IP>:8081/ in a browser and log in as admin with the default password CordysCRM
- Where can I get CordysCRM?
- The source code and installation instructions are on GitHub: https://github.com/1Panel-dev/CordysCRM
Summary generated by AI from the project's README. GitHub stats refresh daily.
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