How It Works

A step-by-step guide to building workflows, configuring nodes, and wiring up variables in AutoPilot.

AutoPilot turns data work into a flowchart. You drag blocks — called nodes — onto a canvas, connect them in order, and click Run. Each node does one job and passes its result to the next. It's the visual version of a command-line pipeline:

cat data.csv | filter "age > 30" | sort by "name" > output.csv

Everything runs inside your browser tab. Nothing is uploaded, no account is needed, and it keeps working with no internet connection.

100% private

Files never leave your machine.

Works offline

Runs fully in the browser, no server.

Handles huge files

Streams to disk so large data won't crash the tab.

The big idea

A workflow is a left-to-right chain of nodes. The output handle of one node connects to the input handle of the next — "send your result onward." A typical CSV pipeline looks like this:

Manual Trigger
Upload File
CSV Parse
CSV Filter

Bring data in → reshape it → export any node's result straight from the execution panel. Mix and match the nodes below to build anything from "dedupe this contact list" to "merge ten PDFs and pull out the tables."

1

Create a workflow

  • Open Workflows from the sidebar.
  • Click New Workflow. Give it a unique name. If you already have workflows, you'll also see a Copy existing option — pick any workflow to use as a starting point, with its full canvas copied over. Otherwise just click Start blank.
  • The canvas opens with a single Start node already placed. Click the tile below it to add your first real block.
  • Workflows auto-save to your browser as you build — click Save in the editor toolbar any time to commit changes explicitly.

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New workflow dialog — start blank or copy an existing workflow as a template.
The New Workflow dialog — name field with Start blank and Copy existing buttons

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Empty editor canvas: the Start node and the dashed + tile ready for your first block.
The empty editor canvas with the initial Start node and dashed + tile
2

Add & connect nodes

  • Click the + button on any node (or the large + tile on the empty canvas) to open the node picker.
  • The very first picker asks "What triggers this workflow?" — pick Manual Trigger (starts when you click Run) or go straight to Upload File.
  • Search or scroll the list, then click a node. It drops onto the canvas already wired to the previous one.
  • Connections run handle-to-handle: the dot on a node's right edge (output) connects to the dot on the next node's left edge (input). Drag between handles to rewire manually.
  • Each node shows a status indicator after a run — no icon when idle, blue spinner while running, green on success, red on error. Use the gear icon to configure or the trash icon to delete a node.

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A simple pipeline: three nodes connected by curved handles.
Editor canvas showing Manual Trigger → Upload File → CSV Parse connected by curved links

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Node picker — search or scroll to find a node, then click to add it.
The node picker panel showing a searchable list of nodes
3

Configure a node

  • Click a node's gear to open its configuration dialog.
  • Most dialogs share the same three-part structure: an input variable (which upstream result to use), the node options (has header, delimiter, sort column, filter conditions, etc.), and an output variable name.
  • Fields are validated with Zod. If something required is missing you'll see an inline message and the Save Configuration button stays disabled until the form is valid.
  • Click Save Configuration — settings are persisted automatically in your browser's IndexedDB.

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Upload File dialog: drop-zone, variable name set to "data", and Save Configuration.
The Upload File configuration dialog with drop-zone and variable name field

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A transform node's dialog: input dropdown, node options, and the auto-suggested output variable name.
A transform node's dialog showing the input-variable dropdown, node options, and output variable name

Variables

Variables are how data travels between nodes. Every node that produces data writes its result to a named variable. The next node picks that name from a dropdown as its input. Think of it as a shared bag of results that grows as the workflow runs.

  1. When you configure Upload File, you give the file a name like data. Downstream nodes can reference it by selecting data in their input-variable dropdown.
  2. CSV Parse reads data and writes a new variable, e.g. parsedData.
  3. CSV Filter reads parsedData and writes filteredData, and so on down the chain.
  4. The output variable name is suggested automatically — when you open the dialog you'll see an auto badge next to the field, showing the suggested name. Simply leave it or type over it to rename. The suggestion is pre-filled — no button needed.
  5. The description below the output name field shows a live preview: {{filteredData}} updates as you type so you can see exactly what downstream nodes will reference.
  6. Column fields (those asking for a header name) autocomplete from the upstream file's schema — once a file is parsed you'll see the real column names as suggestions.
FieldWhat it meansExample
Input variableWhich upstream result this node should readparsedData
Output variable nameNames this node's result for nodes further downfilteredData
{{ variable }}A live preview hint shown in dialog descriptions{{filteredData}}
Column fieldA column header from the upstream file (autocompletes)email, age

Name variables for what they hold (cleanContacts, over30) rather than the node type. When a workflow has ten nodes, descriptive names make the input dropdowns far easier to read.

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The output variable name field: auto-suggested name with the 'auto' badge; edit freely.
Output variable name field with the auto badge and live preview hint

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Column autocomplete: header names pulled from the upstream file's parsed schema.
A column field autocompleting real header names from the upstream parsed file
5

Run & read results

  • Click Run in the editor toolbar. AutoPilot calculates the correct execution order automatically (topological sort) and runs each node in sequence.
  • A progress panel opens on the right. Node indicators turn blue while running and green when done; large files show a live progress bar.
  • If a node fails it turns red with an error message, and the run stops there so you can fix the configuration and re-run.
  • When the run finishes, open the execution panel and click any node's output row to preview it. Hit Export to download the data as CSV, Excel (.xlsx), TXT, or PDF. Toggle "Download in segments" to split very large results into multiple files — either by specifying the number of files or the target rows per file.
  • Every run is saved under Executions in the sidebar — open any past run to see per-node timing, a paginated dataset preview, and to re-download results at any time.

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Progress panel during a run: status dots update live and large files show a per-node progress bar.
Progress panel mid-run showing node list with status indicators and a progress bar

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Execution panel: click Export on any node's output to download as CSV, Excel, TXT, or PDF — with segment options for large files.
Execution panel showing a node's output with the Export button and CSV / Excel / chunk options

Worked example

Filter a contact list down to people over 30 and export it. Three nodes, end to end.

1

Upload File

Drop in
your contacts.csv file
Output variable
data
2

CSV Parse

Input variable
data
Has header
on
Delimiter
auto-detect
Output variable
parsedData
3

CSV Filter

Input variable
parsedData
Condition
age > 30
Logic
AND
Output variable
filteredData
Click Run, then export filteredData from the execution panel — pick CSV or Excel and optionally split into segments.

Node reference

All 21 nodes available in the canvas, grouped by category. Derived from the live node registry — no phantom nodes.

Triggers & input

Manual Trigger

Start the workflow when you click Run.

Upload File

Select a local .csv, .txt, or PDF file and bring it into the workflow.

CSV transforms

CSV Parse

Read a raw file into structured rows and columns, with schema inference.

CSV Filter

Keep only rows matching one or more conditions (12 operators, AND/OR logic).

CSV Sort

Order rows by one or more columns. Uses external merge sort for huge files.

CSV Join

Merge two datasets on a shared key (inner, left, right, full, or cross join).

CSV Aggregate

Group rows by columns and compute totals, counts, averages, min/max.

Detect Duplicates

Find duplicate rows by a key — outputs unique rows and duplicates separately.

CSV Compare

Diff two datasets: produces added, removed, changed, common, and schema_diff sets.

Consecutive Sequence Analyzer

Detect gaps or runs in a numeric or date column (e.g. missing IDs, time gaps).

CSV Transform

Apply conditional find-and-replace rules: replace, clear, delete, or set values.

Column Transform

Apply unconditional ops to a column: trim, case change, regex replace, math.

CSV Restructure

Reorder, drop, or add computed columns to rebuild the output schema.

CSV Generate

Produce a synthetic dataset for testing workflows without real data.

PDF operations

PDF Extract Text

Pull all text from a PDF, page by page.

PDF Extract Tables

Detect tables in a PDF and convert them into structured rows.

PDF Split

Split a multi-page PDF into separate page documents.

PDF Merge

Combine multiple PDFs into one document.

PDF Fill Form

Write values into PDF AcroForm fields.

PDF Generate

Build a new PDF document from text and data.

PDF Sign

Apply a digital signature to a PDF.

Exporting results. There is no export node — run the workflow, then export any node's output straight from the execution panel as CSV, Excel, TXT, or PDF, with segment options for large datasets.

Build your first workflow

It takes about a minute. Add a trigger, drop in a file, chain a couple of nodes, and hit Run.

Open the editor