> ## Documentation Index
> Fetch the complete documentation index at: https://docs.seekr.com/llms.txt
> Use this file to discover all available pages before exploring further.

# What is SeekrGuard

> An overview of SeekrGuard and the workflow for evaluating AI model safety, quality, and risk.

SeekrGuard is a platform for evaluating the safety, quality, and risk of models. It gives reviewers and engineers a shared, evidence-based measure of how a model behaves on data you provide, scored with methods you define and combined into an overall risk assessment.

Use SeekrGuard to determine whether a model meets your requirements for a specific use case and to compare models against one another on the same criteria.

## The evaluation workflow

Most evaluations follow the sequence below, though not every step is required for every review. A quick check might end after an examination, while a formal assessment uses the full sequence.

<Steps>
  <Step title="Register a model">
    Add the models you want to evaluate from a provider. See [Register and manage models](/guard/app/models).
  </Step>

  <Step title="Add a dataset">
    Upload the test inputs to evaluate against, from a file, HuggingFace, or Seekr, and map the dataset's columns. See [Add and manage datasets](/guard/app/datasets).
  </Step>

  <Step title="Choose or build evaluators">
    Select evaluators from the library, or create a custom LLM-as-a-Judge evaluator. See [Create evaluators](/guard/app/evaluators).
  </Step>

  <Step title="Run an examination">
    Combine the dataset, models, and evaluators into a single batch run. SeekrGuard manages the run and reports the scores. See [Run examinations](/guard/app/examinations).
  </Step>

  <Step title="Review the results">
    Review the results across four tabs: model performance, sample responses, interactive analysis, and agentic assessment.
  </Step>

  <Step title="Build risk categories and a profile">
    Optionally, define [risk categories](/guard/app/risk-categories) and weight them into a [risk profile](/guard/app/risk-profiles) to convert raw scores into an overall risk score and risk level for each model.
  </Step>
</Steps>

SeekrGuard also provides two supporting tools. Use the [Chat](/guard/app/chat) page to interact with a model and evaluate a response inline. Use the [Comparisons](/guard/app/comparisons) page to score a single response across several models at once.

## Next steps

<CardGroup cols={3}>
  <Card title="Navigate the app" icon="compass" href="/guard/app/navigate">
    The sidebar layout and the Home page.
  </Card>

  <Card title="Core concepts" icon="cubes" href="/guard/concepts">
    The building blocks you work with in SeekrGuard.
  </Card>

  <Card title="Glossary" icon="book" href="/guard/glossary">
    Definitions of the domain terms used throughout.
  </Card>
</CardGroup>