# Authenta Docs

> Deepfake & Image Forgery Detection Service

## Docs

- [System Architecture](/on-prem/architecture): Authenta On-Prem is built as a **modular, containerized system** that can run entirely within your organization's network.\
All inference processing, task management, and result storage happen locally — ensuring full data confidentiality and compliance.
- [Configuration](/on-prem/configuration): Once Authenta On-Prem is successfully deployed, you can tailor its configuration to match your environment, network policies, and workload requirements.\
This guide explains how to customize Docker Compose profiles, environment variables, message schemas, and data directories.
- [Installation Setup](/on-prem/installation-setup): This guide will walk you through the process of installing Authenta On-Prem in your environment.
- [Introduction](/on-prem/introduction): Welcome to Authenta On-Prem! This documentation will guide you through deploying and using Authenta's deepfake detection system in your infrastructure.
- [Maintenance & Updates](/on-prem/maintenance-updates): This guide provides best practices for maintaining, monitoring, and updating **Authenta On-Prem** after deployment.\
Authenta is designed for long-term, stable operation in air-gapped environments with minimal maintenance overhead.\
You'll only need to enable temporary internet access when applying updates or pulling new container versions.
- [Overview](/on-prem/overview): **Authenta** is an AI-powered media authenticity platform that detects **deepfakes, AI-generated images, and image forgeries** with industry-leading precision.\
It helps organizations verify the integrity of visual content before publication, storage, or legal processing.
- [Prerequisites](/on-prem/prerequisites): Before installing **Authenta On-Prem**, ensure that your system meets the hardware, software, and network prerequisites listed below.\
These requirements are designed to guarantee stable performance, successful image pulls, and full offline operation after setup.
- [Security & Compliance](/on-prem/security-compliance): Authenta On-Prem is designed with **security, privacy, and data isolation** at its core.\
All processing occurs entirely within your infrastructure, ensuring that sensitive media content and detection results **never leave your environment**.
- [Support & Assistance](/on-prem/support): The Authenta team is committed to helping your organization deploy, operate, and maintain the **Authenta On-Prem** system securely and efficiently.\
This page explains how to contact our support team, what information to include when reporting issues, and the scope of assistance available.
- [Troubleshooting](/on-prem/troubleshooting): This page provides solutions to the most common issues you may encounter while deploying or operating **Authenta On-Prem**.\
It covers installation, container runtime, RabbitMQ configuration, GPU setup, and update-related problems.
- [Using Authenta](/on-prem/using-authenta): This guide explains how to use Authenta's detection services through various integration methods.
- [Making API Calls](/api/making-api-calls): This page explains how to correctly interact with the Authenta API after:
- [Base URL](/api/making-api-calls): Your API access request has been **approved**, and
- [Required Authentication Headers](/api/making-api-calls): Your API access request has been **approved**, and
- [Example: GET Request](/api/making-api-calls): Your API access request has been **approved**, and
- [Uploading Media (Two-Step Process)](/api/making-api-calls): Your API access request has been **approved**, and
- [Fetching a Single Media Item](/api/making-api-calls): Your API access request has been **approved**, and
- [Deleting Media](/api/making-api-calls): Your API access request has been **approved**, and
- [Response Structure](/api/making-api-calls): Your API access request has been **approved**, and
- [Error Responses](/api/making-api-calls): Your API access request has been **approved**, and
- [Handling Errors Gracefully](/api/making-api-calls): Your API access request has been **approved**, and
- [Best Practices for API Integrations](/api/making-api-calls): Your API access request has been **approved**, and
- [Summary](/api/making-api-calls): Your API access request has been **approved**, and
- [Next Steps](/api/making-api-calls): Your API access request has been **approved**, and
- [Error Codes Related to Quotas & Credits](/api/quotas-and-credits): **Query Quota** → for `GET` requests
- [Requesting API Access](/api/api-access): Authenta API access is not enabled by default.\
Each **user** must explicitly request access from the Authenta Console, specify their expected usage quotas, and wait for approval from the Authenta admin team.
- [Authentication](/api/authentication): Authenta’s API uses a secure, header-based authentication mechanism.\
Every request must include your **Client ID** and **Client Secret**, which are generated after your API access request is approved.
- [Authentication Error Responses](/api/authentication): **x-client-id** – identifies you
- [Error Handling Flow](/api/authentication): **x-client-id** – identifies you
- [Best Practices for Authentication](/api/authentication): **x-client-id** – identifies you
- [Next Steps](/api/authentication): **x-client-id** – identifies you
- [Authenta .NET SDK](/api/dotnet-sdk): Welcome to the official documentation for the Authenta .NET SDK. This library allows you to integrate state-of-the-art deepfake and manipulated media detection into your .NET applications.
- [Authenta API Overview](/api/introduction): Authenta provides a secure, scalable API that allows customers to integrate deepfake-detection capabilities directly into their own applications and services.\
With API access enabled, you can programmatically upload media, check analysis results, and manage previously processed items using authenticated and quota-controlled API calls.
- [Authenta Python SDK Documentation](/api/python-sdk): Welcome to the official documentation for the Authenta Python SDK. This library allows you to integrate state-of-the-art deepfake and manipulated media detection into your Python applications.
- [Authenta React Native SDK Documentation](/api/react-native-sdk): Welcome to the official documentation for the Authenta React Native SDK. This library allows you to integrate state-of-the-art deepfake and manipulated media detection into your React Native applications.
- [Media API Reference](/api/reference/media): The Media API allows you to create media records, upload media files via a pre-signed S3 URL, fetch media information, and delete media.
- [Supported Models](/api/reference/media): The Media API supports the following operations:
- [Overview](/api/reference/media): The Media API supports the following operations:
- [Authentication](/api/reference/media): **POST `/media`** → Create media record + receive S3 upload URL
- [1. Create Media Record](/api/reference/media): **POST `/media`** → Create media record + receive S3 upload URL
- [2. List All Media](/api/reference/media): **POST `/media`** → Create media record + receive S3 upload URL
- [3. Get a Media Record](/api/reference/media): **POST `/media`** → Create media record + receive S3 upload URL
- [4. Delete Media](/api/reference/media): **POST `/media`** → Create media record + receive S3 upload URL
- [Media Status Lifecycle](/api/reference/media): **POST `/media`** → Create media record + receive S3 upload URL
- [Error Codes](/api/reference/media): **POST `/media`** → Create media record + receive S3 upload URL
- [TypeScript Type Reference](/api/reference/media): **POST `/media`** → Create media record + receive S3 upload URL
- [Summary](/api/reference/media): **POST `/media`** → Create media record + receive S3 upload URL
- [Next Steps](/api/reference/media): **POST `/media`** → Create media record + receive S3 upload URL