What is a Robot?

A Robot is a Transloadit feature that performs one specific file-processing operation, such as resizing an image or encoding a video. Assembly Steps reference Robots by name and connect them to create a custom processing workflow.

Request + files
Results + status
A processing platform accepts an authenticated request, executes a workflow, and returns observable results. This diagram shows platform workflows broadly, not specifically Robots.

How Robots work

Within an Assembly, a Robot represents one processing capability with a documented input contract, parameter set, and result shape. At runtime, the work performed by a configured Step is scheduled as one or more Encoding Jobs. This keeps Robot (the operation), Step (its configured use in the Instructions), and Encoding Job (a runtime execution) distinct. Step names provide the graph nodes, while input selectors connect a Robot to uploads or earlier results, allowing branching and fan-in workflows. The same Robot type can appear in multiple Steps with different configurations. This abstraction lets orchestration describe media work declaratively, while Transloadit schedules the underlying execution and exposes each Step’s outputs.

Key facts

  1. A Robot’s type identifies the operation family, while the user-defined Step name is how other Assembly Steps refer to that configured instance.
  2. One Step can consume results from selected earlier Steps, so changing a dependency can alter both the files processed and when the Step becomes runnable.
  3. Robot outputs retain Step provenance in Assembly results, enabling clients to distinguish an original upload from resized, encoded, inspected, or exported derivatives.

When Robots matter

Select each Robot according to the required operation, then connect its inputs to earlier Assembly Steps. An unsupported input type or incorrect Step dependency can stop processing or produce an unintended result.

Common use cases for platform workflows

These examples cover platform workflows broadly, not specifically Robots.

  • Running repeatable upload, import, processing, AI, storage, and notification pipelines.
  • Tracking long-running media work independently from an application request.
  • Referencing centrally stored credentials by name instead of sending storage secrets with each request.

Working with platform workflows

This guidance covers platform workflows broadly, not just Robots.

A client authenticates and submits files or references together with workflow instructions. The platform validates the request, schedules dependent operations, records state transitions, and exposes results through a response, polling endpoint, or notification.

Platform concepts become reliable only when their lifecycle is explicit. Authentication, idempotency, retries, timeouts, observability, quotas, and terminal states should be designed together rather than added after failures occur.

What you gain

  • Reusable workflows separate application intent from processing infrastructure.
  • Stable job identifiers and lifecycle events improve observability and recovery.
  • Managed queues and workers let products scale without embedding every media tool.

What it costs

  • Synchronous responses are simple but keep connections open while long work executes.
  • Aggressive retries improve recovery from transient faults but can duplicate work or overload a dependency.
  • Higher concurrency reduces queue time until resource contention or a downstream limit becomes the bottleneck.

Before production

  1. Define authentication, authorization, idempotency, retries, and terminal error behavior.
  2. Observe queue time, execution time, callbacks, and partial results with stable identifiers.
  3. Exercise malformed, duplicate, interrupted, and unauthorized requests before launch.

Turn media knowledge into a working pipeline

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