Documentation

MetaLoom is built around two cooperating systems:

Loom manages assets, metadata, users, permissions and pipeline definitions.
Cortex processes media, extracts signals and feeds results back into Loom.

This page is the quickest way to orient yourself in the platform and jump to the right part of the documentation.

Getting Started

Run a full MetaLoom stack locally in minutes using the demo container. Covers Loom UI, Loom App and where to go next.

Loom

The media asset management server. Use these guides when you need the API surface, authentication model, configuration, artifacts or a feature overview.

REST API Java Client Authentication Configuration Artifacts Features Examples

Cortex

The media processing engine. Use these guides when you need node behavior, runtime configuration, deployment options or an overview of supported processing capabilities.

Pipeline Nodes Features Configuration Monitoring API Artifacts Examples

Start Here

If you are new to the platform, this is the shortest reading order:

Start with Getting Started to run a local demo in minutes.
Read Loom and Cortex Interaction to understand the system boundary.
Read Pipeline Mechanism to understand how processing is modeled.
Continue into Loom or Cortex depending on whether you are integrating with the API or building processing workflows.

Central Concepts

The MetaLoom platform revolves around a small set of concepts that appear throughout the documentation.

Asset

The main entity in Loom. An asset represents a file together with metadata, binaries, tags, reactions, comments and derived processing output.

See Loom features

Pipeline

A directed graph of processing nodes. Pipelines describe how Cortex evaluates assets and how results flow between nodes.

See pipeline mechanism

Node

A single processing step such as hashing, OCR, thumbnail generation, face detection, captioning or synchronization back to Loom.

See pipeline nodes

Online vs Offline

Cortex can run standalone against local files or connected to Loom, where it loads pipeline definitions and persists extracted results remotely.

See interaction model

API and Client

Loom exposes a REST API and a Java client for creating assets, authenticating, managing users and orchestrating processing workflows.

REST API · Java Client

Deployment

Both systems ship as JVM artifacts and container images, with Kubernetes deployment paths for server and scheduled batch processing setups.

Loom artifacts · Cortex artifacts

Choose Your Path

Choose the documentation track that matches your task:

Goal	Start with	Then continue to
Try the platform quickly	Getting Started	REST API, Authentication
Integrate a client application with Loom	REST API or Java Client	Authentication, Configuration
Understand how media gets processed	Loom and Cortex Interaction	Pipeline Mechanism, Pipeline Nodes
Deploy or operate the system	Loom Artifacts, Cortex Artifacts	Monitoring, Cortex Configuration
Learn the data model and feature surface	Loom Features	Cortex Features

Goal

Start with

Then continue to

Try the platform quickly

Getting Started

REST API, Authentication

Integrate a client application with Loom

REST API or Java Client

Authentication, Configuration

Understand how media gets processed

Loom and Cortex Interaction

Pipeline Mechanism, Pipeline Nodes

Deploy or operate the system

Loom Artifacts, Cortex Artifacts

Monitoring, Cortex Configuration

Learn the data model and feature surface

Loom Features

Cortex Features

Architecture View

The overall system flow is:

Loom stores asset metadata, user state and pipeline definitions.
Cortex loads or receives work, processes media through pipeline nodes and emits results.
Results are stored locally, sent back to Loom, and exposed through APIs, events and search systems.

For the full interaction model, continue with Loom and Cortex Interaction.