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

# System requirements

> Plan compute, storage, network, and optional GPU requirements.

Presenton resource needs depend on the selected providers, document sizes, concurrent users, and whether AI or image workloads run locally.

## Required for every server deployment

* A supported Docker installation or compatible container platform
* A host port routed to container port `80`
* Persistent storage mounted at `/app_data`
* Outbound network access to every configured hosted provider
* Enough disk space for uploads, generated assets, presentations, and exports
* HTTPS and authentication before exposing the service remotely

## CPU and memory

Start with enough capacity to run the application, document processing, and export together. Large documents, scanned PDFs, concurrent generation, and export increase memory and CPU use. Measure a representative workflow before choosing production capacity.

## GPU

A GPU is optional. It is useful only when a compatible local text or image provider can use it. Hosted providers run in their own infrastructure and do not benefit from a GPU attached to Presenton.

## Network planning

The application must reach configured providers and databases. Clients must reach the web/API port. Publish port `1455` only when the ChatGPT/Codex authentication callback is required.