# **Limitations of Remi in AI: Challenges and drawbacks**

While **[Remi](https://www.remi.ai)** has many benefits for AI developers and researchers, there are also some limitations and challenges to using the framework. Here are some of the drawbacks of using Remi in AI applications:

Performance: One of the main limitations of Remi is its performance. Since it is a web-based framework, the speed of data processing and visualization can be slower compared to other GUI frameworks. This can be a significant drawback for applications that require real-time processing or large data sets.


Limited Functionality: While Remi provides a range of built-in widgets and controls, it may not have all the features required for complex applications. Developers may need to use additional libraries or frameworks to add specific functionality to their applications.

Security: Remi applications are vulnerable to security threats, such as cross-site scripting (XSS) attacks. Developers need to be vigilant and ensure that their applications are secure before deploying them.

Steep Learning Curve: While Remi is relatively easy to learn compared to other GUI frameworks, it still has a steep learning curve for developers who are new to GUI development or web development.

Limited Community Support: Since Remi is a relatively new framework, it has a smaller community compared to other GUI frameworks. This can limit the availability of resources and support for developers who run into issues.

Despite these limitations, Remi is still a valuable tool for AI developers and researchers. Its ease of use, customizability, and integration with other AI frameworks make it a popular choice for building custom interfaces for AI applications. However, developers need to be aware of its limitations and potential challenges, and choose the appropriate framework based on the specific requirements of their project.