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

# Welcome to Plexe

> Build ML models from natural language in minutes

Plexe revolutionizes machine learning development by enabling you to create and deploy high-quality models using natural language instructions. Our intelligent agent system handles data preparation, code generation, training, and deployment—dramatically reducing the complexity of machine learning workflows.

## Plexe Ecosystem

<CardGroup cols={2}>
  <Card title="Python Library" icon="python" href="/library/tutorials/quickstart">
    Open-source library for direct integration into your Python applications. Full control with maximum flexibility.
  </Card>

  <Card title="Managed Platform" icon="cloud" href="/platform/tutorials/quickstart_api">
    Hosted solution with intuitive UI and REST API. Zero infrastructure management with built-in scaling.
  </Card>
</CardGroup>

### Choose Your Path

**Python Library (`plexe`)**

* Integrate directly with Python code via `pip install plexe`
* Control your own compute resources and data
* Bring your preferred LLM provider credentials
* Ideal for: developers, data scientists, ML engineers

**Plexe Platform (`console.plexe.ai` / `api.plexe.ai`)**

* Access via web interface or REST API
* Let us manage infrastructure, scaling, and deployments
* Simplified authentication and billing
* Ideal for: product teams, analysts, organizations seeking enterprise-grade ML

## How It Works

Plexe's multi-agent system powered by Large Language Models works through a sequential process:

1. **Planning:** Analyzes your intent and data to develop a model-building strategy
2. **Code Generation:** Creates appropriate ML code using popular libraries (scikit-learn, PyTorch, TensorFlow)
3. **Execution & Refinement:** Runs the generated code, evaluates results, and iteratively improves performance
4. **Deployment:** Packages the model for inference or deploys it to production infrastructure

## Key Benefits

* **Natural Language Interface:** Describe what you want, not how to build it
* **Rapid Iteration:** Test ideas and create models in minutes instead of days
* **No ML Expertise Required:** Leverage state-of-the-art ML without specialized knowledge
* **Production-Ready Code:** Generate clean, documented, and maintainable ML workflows
* **Full Transparency:** Examine and customize all generated code

Ready to start building? Choose your preferred approach:

* [**Python Library Quickstart**](/library/tutorials/quickstart)
* [**Platform API Quickstart**](/platform/tutorials/quickstart_api)