Oinone, an AI-powered enterprise-class productization engine under Shushi Tech, serving as an integrated R&D framework for standard product development and agile delivery based on low-code and no-code technologies. Focused on addressing the productization transformation needs of software companies, it resolves the long-standing industry dilemma of fragmented standardized product development and customized delivery through its integrated "Standardized R&D + Agile Delivery" architecture.
The "O" symbolizes open source while phonetically resonating with "All in one," symbolizing:
- One-stop solutions
- Agile responsiveness
- Continuous innovation
We are committed to building an open low-code/no-code ecosystem that creates value for clients while empowering developers. Through our "co-creation" philosophy, we aim to aggregate collective wisdom and resources, fostering innovation and development for Chinese developers to help every idea flourish within our ecosystem.
Mission：To establish the foundational technology platform for intelligence software products, driving industry transformation, empowering partners, and creating customer value.
Comprehensive coverage of product development and implementation needs.
- 🌟 Who it solves problems for ?
- Designed for software companies as a foundational technology platform, it aims to drive industry transformation and provide support for partners. Currently serving nearly 100 software companies, including leading industry players such as Jack Technology (the world's largest provider of intelligent connected solutions for garment production), Shanghai Mathart System (a renowned software provider in China's automotive industry), and Goodfull Cloud (China's leading provider of union welfare software).
- 🌟 What problems it solves ?
- Empower software companies to fully embrace AI, ensure the stability of AI output quality. More importantly, it helps software companies with productization aspirations overcome challenges in product standardization and agile delivery.
- 🌟 Enterprise-Grade Vibe Coding Best Practices
- Standardization: Serve as a standard to avoid the issues of "poor maintainability" and "black-box nature" in code generated by Vibe Coding.
- Open Source: Enable AI to quickly learn the design principles and development paradigms of enterprise-grade low-code.
- AI Agents: Provide dedicated front-end and back-end intelligent agents to ensure the stability of AI output quality.
- 🌟 Applications inherently feature a "Data-Feedback Loop (DFL)" mechanism, fostering a "self-evolving" application growth model.
- Build the full lifecycle capabilities of AI employees covering [Training → Modeling → Execution → Evaluation → Autonomous Execution].
- Get the latest code from github.com/oinone.
- Join the community: Go to [Oinone Community] ❤️
- How to contribute
- Oinone repository is licensed under AGPL-3.0.
- Third Party Open Source Software and License Notice
- Website: https://www.oinone.top
- Email: oinone@shushi.pro