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This guide walks you through creating a workflow in the Omni dashboard. A workflow defines your verification logic — the policy, engines, and output format — that Omni applies every time you run an analysis.

Prerequisites

Before you begin, make sure you have:
Each project supports up to 10 workflows. If you need more, create an additional project.
Workflow list empty state

Workflow List — if no workflows exist yet, use + Create New Workflow to start.

Workflow Creation Steps

Creating a workflow involves four steps in the dashboard. Each step builds on the previous one.
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Step 1: Basic Info

Start by giving your workflow a name and an optional description.
  • Name — A short, descriptive label for the workflow (e.g., “Invoice Review”, “Vendor KYB Check”). This is how you will identify the workflow in the dashboard and API responses.
  • Description — A brief summary of what this workflow does. This is for your team’s reference only and does not affect how Omni processes documents.
Workflow creation Step 1 - Basic info

Step 1: Enter a workflow name and description.

Use naming conventions that reflect the document type and verification purpose. For example: “Invoice - Amount Validation” or “KYB - Business Registration”. This makes it easier to manage multiple workflows in a project.
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Step 2: Policy Definition

Write a natural language policy that describes what Omni should verify. This is the core of your workflow — it tells the AI agent what to check, what to extract, and how to make decisions.Your policy should include:
  • The type of documents you expect
  • Specific verification steps (what to check)
  • Pass/fail criteria (what constitutes approval vs. rejection)
Example policy:
Workflow creation Step 2 - Policy definition

Step 2: Write your verification policy in natural language. Optional policy documents can be uploaded.

Vague policies produce vague results. Be specific about what documents to expect, what fields to check, and what your approval criteria are. See the Policy Writing Guide for detailed best practices.
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Step 3: AI Model Selection

Choose the AI model the workflow will use.
Workflow creation Step 3 - AI model selection

Step 3: Choose the AI model the workflow will use.

You do not pick verification engines here. They are selected automatically from the policy, and you can see which ones a workflow ended up with under engines in GET /workflows/:workflowId. For what each engine does, see Engines.
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Step 4: Output Schema

Define the JSON structure for the results you want back. This tells Omni exactly what format to return after analysis — field names, data types, and structure.Example output schema:
Use the Field Builder tab to add fields visually, or JSON Schema Input to edit the schema as JSON. The Schema Writing Guide at the bottom of the step summarizes Draft-07 rules and Omni constraints (see Output Schema).
Workflow creation Step 4 - Field Builder tab

Step 4 — Field Builder: define fields, types, and descriptions. Use JSON Schema Preview to validate.

Workflow creation Step 4 - JSON Schema Input tab

Step 4 — JSON Schema Input: edit Draft-07 JSON Schema directly; stays in sync with Field Builder.

We recommend a decision block with a result field, verificationStatus, and a reasons array. The system does not enforce this structure, and the field is user-defined — separate from the top-level system verificationStatus. Matching the system enum (verified / pending_review / rejected) keeps downstream routing simple. See the Output Schema documentation for more details.
Workflow created successfully confirmation

After you finish Step 4, Omni shows a confirmation with your playbook ID and a summary of playbook actions.

Align terminology across policy, Item names, and JSON output schema

Whenever you rely on specific technical terms or verification targets (such as document types), use the same wording in all three places below. For example, if the policy says you will review a business registration certificate, register the Item under the same label (e.g. the equivalent term your team uses consistently in Korean or English), and use that same term in the output schema where you describe validation for that document. That alignment helps the agent connect policy, uploaded files, and structured results reliably. In a customer-defined JSON output schema, keep descriptions and context for specific values aligned as well. For instance, if a field such as document_validation is true, the surrounding description should refer to the same document type (e.g. business registration) and clarify what “sufficient information” means (company name, address, representative, and other fields expected on that document).
At runtime, whenever you add an Item, set item.name (or the Item name field in the API) to match the policy wording and the terminology used in your JSON output schema. If these diverge, the agent may map documents and fields incorrectly.
Profile Data Objects tab with item names

Data Objects — Item names shown here (e.g. business registration certificate) should match your policy and output schema.

After Creation

Once you complete all four steps, your workflow is ready to use. You can open it from the workflow list to manage profiles and analyses, or review policy, engines, and output schema from the workflow configuration view.
Workflow detail page with profile list

Workflow detail — profiles, analyses count, and Workflow modification.

Workflow settings with policy, engines, and JSON output schema

Workflow configuration — Policy definition, selected engines, and JSON output schema (after creation or via edit).

Using Your Workflow via the API

With your workflow created, follow this flow to run verifications:
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Create a Profile

Each verification case (e.g., one invoice, one vendor) gets its own profile under the workflow.
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Upload Documents

Upload the documents to be verified into the profile’s folder.
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Wait for ACTIVE Status

Poll the item status until all uploaded documents reach ACTIVE status. This means OCR and text extraction are complete.
Poll at 1-second intervals with a 60-second timeout. Do not trigger analysis until all items are ACTIVE.
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Trigger Analysis

Run the analysis. Omni applies your policy, engines, and output schema automatically.
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Retrieve Results

Fetch the structured results that match your output schema.
For the complete API flow with detailed request/response examples, see the Quickstart guide.

Tips for Success

If your use case matches one of the workflow templates (KYB, Invoice, AML, Compliance), start there and customize. It is faster than building from scratch.
After creating a workflow, run a few test profiles with actual documents to validate that your policy and schema produce the results you expect. Adjust as needed.
Your first policy draft may not be perfect. Review the analysis results, identify where the AI misunderstood your intent, and refine the policy language. Small wording changes can significantly improve accuracy.
Design your output schema to match what your backend or compliance system expects. This eliminates the need for post-processing transformations.

What’s Next?

Policy Writing Guide

Learn best practices for writing effective verification policies.

Workflow Automation

Transform your manual review processes into automated workflows.