> For the complete documentation index, see [llms.txt](https://docs.rierino.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.rierino.com/data-science.md). # Data Science - [Data Science Overview](https://docs.rierino.com/data-science/data-science-overview.md): Rierino provides low/no-code capabilities for customizing and managing data science models. - [GenAI Models](https://docs.rierino.com/data-science/genai-models.md): In addition to general ML models, Rierino provides facility for governing LLM models for GenAI use cases - [AI Agent APIs](https://docs.rierino.com/data-science/genai-models/ai-agent-apis.md): All AI agents configured on Rierino are automatically accessible as APIs and can be incorporated into any app for visual interaction - [AI Guardrails](https://docs.rierino.com/data-science/genai-models/ai-guardrails.md): Configure multi-stage safety checks for AI agents using risk policies, regex rules, judge models, saga processors, and reusable presets - [Useful Checks](https://docs.rierino.com/data-science/genai-models/useful-checks.md): This section explains most common errors and the checks to perform for troubleshooting - [MCP Servers](https://docs.rierino.com/data-science/mcp-servers.md): In addition to full scale GenAI models, Rierino provides facility for creating MCP servers utilizing already existing functionality - [ML Models](https://docs.rierino.com/data-science/ml-models.md): ML model configurations allow central listing and management of all data science models. - [Scheduler Platforms](https://docs.rierino.com/data-science/ml-models/scheduler-platforms.md) - [Airflow Scheduler](https://docs.rierino.com/data-science/ml-models/scheduler-platforms/airflow-scheduler.md): Models can be scheduled on Airflow for automated DAG creation and execution. - [Complex Event Processing](https://docs.rierino.com/data-science/complex-event-processing.md): Data flows provide a standardized form of defining data integration flows, which can easily be migrated between systems. - [Siddhi Data Flows](https://docs.rierino.com/data-science/complex-event-processing/siddhi-data-flows.md): These queries are converted to Siddhi statements by SiddhiCodeProducer. - [Data Visualizations](https://docs.rierino.com/data-science/data-visualizations.md): Visualizations are used for embedded dashboards and reporting. - [Data Science FAQ](https://docs.rierino.com/data-science/data-science-faq.md): This FAQ covers the core Data Science concepts, model governance approach, and when to use ML, GenAI, MCP, CEP, and visualizations --- # 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.rierino.com/data-science.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.