> ## Documentation Index > Fetch the complete documentation index at: https://docs.oumi.ai/llms.txt > Use this file to discover all available pages before exploring further. # OVERVIEW > Introducing the Oumi workflow The Oumi Agent is your primary collaborator for building custom AI models. Using natural language prompts, it orchestrates the full model development lifecycle from [dataset creation](/guides/datasets/create) to [training](/guides/training), [evaluation](/guides/evaluations), and [deployment](/guides/deployment), so you can move from problem to production in hours instead of weeks. By selecting the right model size, configuration, and training strategy for your task, the Oumi Agent helps reduce inference costs and latency while keeping quality high. It also works continuously in the background to surface missing configurations, flag potential issues, and keep your workflow on track, allowing you to stay focused on outcomes, not setup. At every stage, you retain full control over how each step is run. ## THE OUMI UI After logging in and selecting a project, you will be taken to Oumi’s main interface, where you can see a high level overview of your project’s artifacts and access quick actions for common tasks. The left-hand navigation contains links to each one of the main sections in the Oumi platform: * **Overview:** The main landing page for your project's artifacts. * **Datasets:** Import existing data or generate new datasets for training and evaluation. * **Evaluators:** Define metrics and judges used to score model outputs, including accuracy, safety, and task success. * **Evaluations:** Run evaluations to score models on your datasets using your evaluators. Compare candidates, inspect failure modes, and track progress over time. * **Models:** Train models using datasets and insights from completed evaluations. * **Recipes:** Reusable configurations and settings. * **Files:** Additional data for grounding your responses. * **Activity log:** A list of historical and currently running jobs.