ChatGPT is leading platform for chatting with OpenAI's language models. The code interpreter feature was revolutionary when it came out and showed us what is possible when large language models and combined with code execution capabilities. However, using ChatGPT alone for your data analysis tasks is limiting for several reasons.
In this article, we compare ChatGPT and Keptune AI and focus on five key aspects: pricing structure, AI model selection, code execution capabilities, and workflow integration.
In the free version of ChatGPT, you will be locked out of data analysis features until the next day when rate limits are enforced. Keptune AI offers a more reliable free tier and a more affordable paid plan because its efficient browser-based code execution reduces the need for additional computational resources. This pricing structure makes Keptune AI accessible to a wider range of users, from beginners to professionals.
Keptune AI can chose between models provided by various provides like OpenAI, Anthropic, and Google. It employs an automated model selection process by analyzing the given task to choose the most appropriate AI model based on extensive benchmarking of various use cases. This approach simplifies the user experience and potentially improves analysis outcomes by leveraging the platform's expertise in model selection.
With ChatGPT, you only have access to the OpenAI models. It requires users to manually select and experiment with different AI models. While this offers more control, it also demands a higher level of expertise from the user. The process of finding the optimal model can be time-consuming, counts towards usage limits, and may lead to suboptimal results if the user is not well-versed in the strengths and weaknesses of various models.
The automated approach of Keptune AI is particularly beneficial for users who want to focus on data interpretation rather than model selection technicalities. It also reduces the risk of choosing an inappropriate model, which could compromise the analysis results.
Code runs in the user's browser, eliminnating the need to transfer all data to the server and paying for extra compute resources.
Keptune AI's approach to code execution offers several advantages. The ability to write and run unlimited Python code blocks provides greater flexibility and control over the analysis process. Users can implement custom functions, import specific libraries, and fine-tune their analysis beyond what AI-generated code might offer.
The browser-based execution in Keptune AI also enhances privacy, as only a limited fraction of data is sent to external servers support in planning and code generation.
With ChatGPT, users cannot edit or rerun the AI-generated code so users are limited in their options to customize the code and output to fit their needs.
Keptune AI's integrated approach to workflows streamlines the analysis process. By treating every chat as a potential workflow, it reduces the overhead of setting up separate workflows for each analysis task. Users can simply upload new data files and rerun entire analysis with a single click.
Both Keptune AI and ChatGPT offer valuable features for data analysis, but they cater to slightly different user needs and preferences.
Keptune AI stands out with its:
ChatGPT may be preferable for users who:
Ultimately, the choice between Keptune AI and ChatGPT will depend on your specific needs, budget, and workflow preferences. Keptune AI's combination of affordability, automation, and flexibility makes it a strong contender, especially for users looking to optimize their data analysis process while maintaining control over their code and costs.
By offering a more accessible pricing structure, automated model selection, and browser-based code execution, Keptune AI positions itself as a cost-effective and efficient solution for a wide range of data analysis tasks.