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Usage Modes

Overview​

When working with Rhombus AI Pipeline, you can choose between two usage modes based on your workflow:

  • AI-Assisted Mode — Use the built-in AI agent to automatically create and configure pipelines via natural language instructions. (Recommended for most users.)
  • Manual Mode — Build and configure pipelines step by step, giving you full control over transformations, data flow, and outputs.

If you are new to Rhombus AI, we recommend starting with AI-Assisted Mode.

For advanced use cases or debugging complex datasets, Manual Mode provides greater flexibility.

Mode 1 — AI-Assisted Mode (Recommended)​

The AI-Assisted Mode helps you build pipelines faster using the built-in AI Chatbot.

Simply describe your request in plain language, and the AI agent will create, configure, and run your pipeline automatically — saving you time and reducing manual setup.

tip
  1. For a complete walkthrough, check the Pipeline Quick Start Guide.

AI Assistant Mode

Mode 2 — Manual Mode (Advanced)​

The Manual Mode lets you create and configure pipelines step by step, giving you complete control.

Manual Configuration Mode

Step 1 — Create a Project​

Before uploading your dataset, make sure you have a project to work in.

If you haven’t created one yet, follow Step 1 — Create Your First Project from the Quick Start Guide.

tip

The Data Input node is the entry point of your pipeline. Without it, no data can flow into the system.

Step 2 — Add Your First Node​

  1. Click the “+ Add Node” button on the canvas.
  2. A Node Palette will appear, showing all available node types.
  3. The first node must be a Data Input node, since every pipeline begins with data.
  4. Drag and drop the Data Input node onto the canvas.
tip
  1. The Data Input node connects your dataset to the pipeline.
  2. Without it, downstream transformations won’t have any data to process.

Add Your First Node

Step 3 — Upload Your Dataset​

  1. Select the Data Input node on the canvas.
  2. In the Upload Data panel, choose one of the following:
    • From Device — Upload a dataset (CSV or XLSX) from your local computer.
    • From Other Sources — Import from a supported cloud source (currently supports AWS S3).
  3. The uploaded dataset is stored in the project database and will be available for selection in the next step.
tip
  1. Free plan users can upload files up to 10 MB per file, with a maximum total size of 50 MB.

datasource

Step 4 — Bind Your Dataset​

  1. Open the Data Input node’s configuration panel on the right.
  2. In the Select Dataset menu, choose the dataset you want this pipeline to use.
  3. The selected dataset will be linked to the Data Input node and made available for downstream transformations.

Example:
If you uploaded Iris.csv, it will appear in the Select Dataset menu and can be selected for this pipeline.

tip
  1. The Select Dataset menu lists all datasets stored in the project database.
  2. You can upload multiple datasets within a project, but each Data Input node can only be bound to one dataset.

Bind

Step 5 — Add a Transformation Node​

After configuring the Data Input node, you can add your first transformation node:

  1. Click “+ Add Node” and select a transformation, such as Sort Data, Remove Duplicates, Text Cleanup, or Normalize Data.
  2. Drag the selected node onto the canvas and place it to the right of the Data Input node.
  3. Connect the output port of the Data Input node to the input port of the transformation node.
  4. Configure the parameters of the transformation node in its configuration panel.
tip
  1. Each transformation node has its own configurable parameters.
  2. For detailed parameter descriptions, see the Transformer References.

Bind

Step 6 — Build a Complete Pipeline​

To create a complete pipeline, repeat Step 5 to add and connect multiple transformation nodes:

  1. Click “+ Add Node” to add additional transformations.
  2. Drag nodes onto the canvas and arrange them in the correct sequence.
  3. Connect the output of each node to the input of the next to define the data flow.
  4. Configure the parameters for each transformation node to ensure correct processing.
  5. Continue until your pipeline includes all required transformations.
tip
  1. Pipelines can include one or many transformation nodes chained together to build complex workflows.

Step 7 — Run & Preview Your Pipeline​

After building and configuring your pipeline, run it manually and preview the results:

  1. Click the last node on the canvas.
  2. In the configuration panel, click Apply to run the pipeline.
  3. Once the run is complete, open the Preview tab of the last node to review the processed dataset.
tip
  1. Always review the output in the Preview tab before downloading.

preview

Step 8 — Download Your Dataset​

Once you’ve verified the results, download the processed dataset:

  1. In the Preview tab of the last node, click Download Dataset.
  2. Choose your preferred format:
    • CSV
    • Excel (XLSX)
tip
  1. The downloaded file contains the final processed dataset.
  2. If the results are unexpected, adjust your transformations, re-run the pipeline, and preview again before downloading.

download