> ## 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.

# Key Concepts

This page defines the core terminology used across Avigrah. These concepts describe how the platform structures environments, executes AI, and enforces governance.

| Term                                 | Description                                                                                                                                                                                                           |
| :----------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Organization                         | A top-level tenant representing a single business entity. All data, projects, and executions are isolated per organization.                                                                                           |
| Project                              | A scoped unit within an organization that runs a specific **AI Template**, with defined data pipelines, AI Template, Clear business goal and assigned teams. All AI execution is contained within a project boundary. |
| Environment                          | An execution context (**Core** or **Apex – sandboxed infra**) that separates risk, configuration, and responsibility for AI workflows.                                                                                |
| Sandboxing                           | An isolated environment used for AI systems. This adds an extra layer of security and ensures data isolation thorugh the Apex Environment. **This is not for testing purpose like traditional means.**                |
| Core Environment                     | The primary operational environment for stable and approved AI workflows serving business-critical use cases.                                                                                                         |
| Apex Environment                     | The highest-trust environment used for fully validated, production-grade AI execution and external system integrations.                                                                                               |
| Data Pipeline                        | A defined flow that ingests, processes, transforms, and prepares data for AI reasoning and execution.                                                                                                                 |
| AI Template                          | A scoped AI template designed to solve a specific business problem (e.g., customer segmentation). An AI Template typically consists of multiple AI agents working together in a coordinated workflow.                 |
| AI Agent                             | A specific AI entity responsible for performing a single, well-defined task, such as generating reports or executing controlled changes in external integrations.                                                     |
| RAG (Retrieval-Augmented Generation) | A governed context-retrieval system that uses Retrieval-Augmented Generation to supply approved, project-scoped business data to AI Images during execution.                                                          |
| Standard RAG System                  | The platform implementation of Retrieval-Augmented Generation that supplies governed, project-scoped business data as execution context to AI Images.                                                                 |
| Task Execution                       | A single run of an AI workflow within a project, tracked with state, progress, inputs, outputs, and metrics.                                                                                                          |
| Execution Control                    | The ability to start, pause, retry, stop, and monitor executions to ensure operational safety and reliability.                                                                                                        |
| Integration                          | A controlled connection to external systems such as CRM, ERP, global commerce, platforms, or marketing tools, executed only through approved workflows.                                                               |
| Isolation                            | Enforcement of strict separation across organizations, projects, and environments to prevent data leakage and cross-tenant risk.                                                                                      |
| Observability                        | Visibility into AI behavior through logs, metrics, status, and performance indicators for debugging and compliance.                                                                                                   |
| Roles                                | Predefined permission sets that determine what actions a collaborator can perform within an organization, project, or environment.                                                                                    |
| RBAC                                 | A security mechanism that enforces scoped access across AI environments by mapping roles to permitted actions and resources.                                                                                          |
| Teams                                | A group of users assigned to a project who interact with, operate, and consume AI workflows and outputs.                                                                                                              |

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