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Instead of calling automation steps one by one and writing glue code between them, a Workflow defines the sequence once. The output of each step flows automatically into the next. Trigger the whole pipeline with a single action and inspect every step’s output in one run history view.

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How Workflows are structured

A Workflow is an ordered list of steps. Each step type has a distinct role:

Agent Step

Runs an autonomous browser agent that navigates a site, fills forms, clicks through pages, and extracts data. This is the browser-automation core of any Workflow.

Code Step

Runs Python in a secure cloud sandbox. Use it to process, transform, or enrich data returned by an Agent step — or to call any library that doesn’t need a browser.

HTTP Step

Makes an outbound REST call — GET, POST, PUT, or DELETE — to any external endpoint. Use it to call webhooks, write to third-party APIs, or trigger downstream services.

Transform Step

Reshapes or filters data between steps using built-in operations: map, filter, pick, or wrap. Runs entirely in Valendata’s runtime — no external calls, no side effects.

Skill Step

Executes a published Skill and passes parameters to it. Use when you have already recorded and published the automation as a reusable Skill.

dfuse Step

Connects to Slack, Gmail, Notion, and Postgres through the dfuse integration layer. Use it to read or write to these services without building custom HTTP calls.

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Building a Workflow

Workflows are built on a visual canvas. Open Workflows in the sidebar, create a new Workflow, and use the Brain agent chat to describe what you want to build. The Brain adds, configures, and tests steps for you. You can also add steps manually from the canvas toolbar and configure each step’s settings directly. The Brain agent can:
  • Add any step type to the canvas
  • Write and test code for Code steps
  • Configure HTTP steps with the correct URL, method, and body
  • Wire step outputs into downstream step parameters

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Passing data between steps

Steps communicate through a simple template syntax: {{path.to.value}}. Any step config field can reference the output of a previous step or a Workflow-level input. Each step’s id is set when the step is created. Reference any previous step by that id — the Brain sets these automatically when building your Workflow.

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Credentials in HTTP steps

To authenticate HTTP steps without hardcoding secrets, store your credentials in Credentials (in the sidebar), then reference the credential by its ID in the step config via the credential_id field. Valendata injects the credential into the request headers at run time — the value is never logged or exposed in the run history.

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Triggering a Workflow

From the dashboard — open the Workflow and click Run. Fill in any input values and watch step outputs appear as each step completes. On a schedule — go to the Schedules page and create a new schedule, selecting the Workflow as the target. Choose a preset cadence or enter a custom one. The Workflow runs automatically at each scheduled time and results appear in the Run history. Via webhook — each Workflow can be given an inbound webhook URL. POST to the URL with a JSON body and Valendata runs the Workflow using the body as its inputs. Configure the webhook and its secret in the Workflow’s trigger settings.

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Step output and run history

Every execution creates a Run record. Open a Workflow, go to the Runs tab, and click any run to inspect:
  • Overall status (success, failed, partial)
  • Per-step output and execution time
  • Full browser replay for any Agent step that opened a browser session
Skill steps inside a Workflow consume credits independently — once per Skill execution. HTTP and Transform steps do not consume credits. Agent and Code steps consume credits based on browser session time and sandbox usage respectively.

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A realistic example

A competitive pricing pipeline that runs every morning:
  1. Agent step — navigates competitor product pages and extracts an array of prices
  2. Transform step (filter operation) — keeps only products where the competitor price is below your threshold, passed in as {{inputs.your_price}}
  3. HTTP step — POSTs the filtered list to a Slack webhook for immediate review
  4. HTTP step — writes every price record to an internal API endpoint, referencing a stored credential via credential_id