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

# Quick Start

This guide provides a minimal overview of how to start using Avigrah to run AI workflows within a governed, production-ready environment.

### 1. Create an Organization

An Organization is the top-level isolation unit in Avigrah.

* Represents a single company or client
* Owns all projects, data, pipelines, credentials, and usage
* Ensures complete data, execution, and billing isolation

All resources in Avigrah exist within an organization.

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### 2. Invite Collaborators

Invite users to collaborate within your organization.

* Roles define what actions each user can perform
* Access is enforced across projects, pipelines, and AI execution
* Users can only access resources within their assigned scope

Permissions are enforced at runtime, not just in the UI.

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### 3. Create a Project

A Project defines a specific AI use case and its execution boundary.

* Select an AI Template (e.g., Customer Intelligence, Ads Conversion, Investor Intelligence)
* Defines scope for:
  * Data pipelines
  * Vector stores
  * AI agents
  * Teams

Each project ensures AI operates only on approved data.\
**One project = one AI workload.**

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### 4. Create a Team

Teams define who can access and use the AI.

* Add users to teams
* Assign teams to projects
* Team members can only access outputs within assigned projects

Teams represent AI consumers, not infrastructure owners.

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### 5. Create a Data Pipeline

Pipelines prepare data for AI execution.

* Supports batch and real-time data sources
* Executes in ordered phases:\
  **Ingest → Transform → Store → Vectorize → Ready for AI**
* Outputs are stored in project-scoped storage and vector databases

AI agents consume processed pipeline outputs, not raw data.

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### 6. Create an Integration

Integrations connect external systems to Avigrah.

* Configure third-party or internal system credentials
* Credentials are stored at the organization level
* Assign integrations to specific projects

Pipelines and agents can now access live operational data securely.

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### You're Ready To Go

Your environment is now fully configured.

* Data pipelines are active
* AI agents can execute securely
* Access is controlled via roles and teams
* Usage is tracked per organization and project

You can now start generating insights, automation panel, and AI-driven workflows.