> For the complete documentation index, see [llms.txt](https://docs.raga.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.raga.ai/ragaai-prism/test-inventory/event-detection.md). # Event Detection #### Event Detection The goal of AI end-to-end pipeline testing is to validate and assure the smooth operation of the complete artificial intelligence workflow, which includes data preprocessing, model training, inference, and output interpretation. This comprehensive testing approach gives a holistic understanding of the model's performance and is used in a variety of industries, including finance for risk assessment, healthcare for patient diagnostics, manufacturing for quality control, and natural language processing for sentiment analysis in customer service. RagaAI ensures that these models can accurately differentiate and label the components of an image, detect drift and performs well in diverse scenarios. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://docs.raga.ai/ragaai-prism/test-inventory/event-detection.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.