> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://mediakind.ferndocs.com/mkio/understanding/core-concepts/vod-processing/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://mediakind.ferndocs.com/_mcp/server.

# Video Processing

Re-encode, transform, or enhance your video assets

MK.IO’s Video-on-Demand (VOD) encoding allows you to process video files into various formats and bitrates, ensuring optimal playback quality and compatibility across different devices and networks.

## Concepts

MK.IO’s video processing is built on two primary components: **Transforms** and **Jobs**.

#### Transforms

A **Transform** defines the specific processing instructions that will be applied to your media. There are several categories of transforms available:

* Encoding Transform: Single-bitrate and multi-bitrate transforms that transcode your video into H.264 or H.265 content, with resolutions ranging from SD to 4K.

* AI pipeline transform: Runs an AI pipeline against your content, covering transcription, translation, and dubbed-audio generation.

* Asset Conversion Transform: Enables format conversion from various live event or VOD assets into the latest MP4 format supported by MK.IO.

* Thumbnail generation transform: Generates individual thumbnails, sets of thumbnails, or sprite files for video assets.

* Track insertion transform: Adds new tracks to a VOD asset and automatically updates the client and server manifests.

These are the only transform types available. A Transform’s output is limited to one of these preset types per output.

#### Jobs

A **Job** is the actual request to apply a specific Transform to an input asset. The Job processes the input data and outputs the results to a specified destination asset. See [Transforms & Jobs](/mkio/understanding/core-concepts/transforms-and-jobs) for job states, input types, and priority.

## Docs

- [AI workflows](https://mediakind.ferndocs.com/mkio/understanding/core-concepts/vod-processing/ai-workflows.md)