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Overview

Creating a Pipeline in Adopt AI is a three-step wizard followed by an AI-generated workflow you can refine before activating. The entire process takes about five minutes. This guide walks through building a pipeline called QuickBooks Expense Aggregation as an example.

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Step 1 — Navigate to Pipelines

From the left sidebar, navigate to the Pipelines. You’ll land on the All Pipelines list. This shows all pipelines in your current project, along with their status, data source, schedule, and last update.

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Step 2 — Start a New Pipeline

Click the + New Pipeline button in the top-right corner. Screenshot2026 03 30at9 54 30PM The Create Pipeline wizard opens. It has three steps shown at the top: Source → Schedule → Describe.

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Step 3 — Configure the Source (Step 1 of 3)

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3.1 Name your Pipeline

Enter a descriptive name in the Pipeline Name field. Choose something that clearly conveys the data being extracted and its purpose. Examples:
  • QuickBooks Expense Aggregation
  • HubSpot Deal Sync
  • Salesforce Account Overview

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3.2 Select your data source

Choose how data will be sourced:
  • Connectors — pull data from an external system (HubSpot, AWS S3, QuickBooks, etc.)
  • Internal Data Store — read from data already stored in Adopt AI
For most pipelines, you’ll use Connectors.

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3.3 Select a Connector

Under Source Connector, you’ll see your available connectors. Click a connector card to select it. Screenshot2026 03 30at9 55 41PM When a connector is selected, a confirmation banner appears.
If you don’t have a connector for your data source, click + New Connector or “Create a new connector →” to set one up.
At the bottom of the page, a notice confirms: “Data syncs to Internal Data Store — All pipeline data will be stored in your dedicated internal storage for dashboards and export.” Click Next → to proceed.

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Step 4 — Set the Schedule (Step 2 of 3)

Screenshot2026 03 30at9 56 44PM Choose how often the pipeline should run:
OptionWhen to Use
ManualRun on-demand only; useful for one-off extractions or testing
HourlyData needs to stay fresh throughout the day (e.g., CRM deals)
DailyMost common for reporting and analysis pipelines
WeeklyLower-frequency aggregations (e.g., weekly financial summaries)
CustomEnter a cron expression for fine-grained control
Custom schedule reveals a Cron Expression field. For example, */15 * * * * runs every 15 minutes. Screenshot2026 03 30at9 58 46PM
For most analytics and reporting pipelines, Daily is the right choice. Use Hourly when agents need fresh data throughout the working day.
Click Next → to proceed.

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Step 5 — Describe the Pipeline (Step 3 of 3)

Screenshot2026 03 30at9 59 58PM This is where Adopt AI’s AI capability comes in. Rather than manually configuring each extraction and transformation step, you describe what you want the pipeline to do in plain English. In the text area, write a description that includes:
  • What data to extract
  • Any filters or conditions
  • How to transform or aggregate the data
  • What the final output should look like
Example description: 
Pull all expense records from the data source. Filter to only include expenses
over $500. Aggregate by category and store the results as a structured table.
You can also include branching logic: 
Pull deals > $10K. AI score risk. High risk → Slack + sub-branch by size.
Medium → store + email. Low → store.
Click ✦ Create to generate the pipeline.

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Step 6 — Review the AI-Generated Workflow

After clicking Create, Adopt AI generates a complete workflow from your description. The pipeline enters Draft status while the AI builds the workflow graph. Screenshot2026 03 30at10 08 55PM The generated workflow will appear as a Workflow Graph with connected nodes. Based on your description, nodes might include:
  • READ DB — pulls data from your connected source
  • FILTER — applies your filter conditions
  • GROUP / TRANSFORM — aggregates or reshapes the data
  • WRITE — stores the final output as a named Pipeline Outcome
Screenshot2026 03 30at10 09 59PM

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Refining the Pipeline

In Draft state you can:
  • Edit the description in the “Describe & Refine” text area and click Regenerate to create a new workflow
  • Click individual nodes to inspect their configuration (fields and JSON view)
  • Toggle Dev Mode to inspect the raw workflow definition
  • Run a Test Run to validate the pipeline before activating
Always run a Test Run before activating a pipeline in production. This validates that your connector credentials are correct and the workflow produces the expected output.

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Step 7 — Activate the Pipeline

When you’re satisfied with the workflow, click the Activate button (top-right or within the Workflow Graph header). The pipeline will:
  1. Change status from Draft to Active
  2. Begin running immediately on its first execution
  3. Continue running on the schedule you defined
Once active, the pipeline detail view gains additional tabs: Overview, Runs, and Data — where you can monitor execution health and preview output records.

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What Comes Next?

Your pipeline is now running and producing data. Here’s what to do next:
  • View run history on the Runs tab — see every execution with its start time, duration, and status
  • Preview the output data on the Data tab — inspect the Pipeline Outcome table
  • Connect it to an Agent — add a Pipeline node in your agent canvas to give the agent access to this data
  • Bind it to an Experience — surface the data in a HITL dashboard for human reviewers
See Pipeline Features for a full reference of all pipeline capabilities.