Policy Writing Guide

Your policy is the most important part of an Omni workflow. It tells your Review Ops Agent exactly what to check, how to evaluate documents, and when to approve or reject. A well-written policy produces accurate, consistent results. A vague one produces unreliable output. This guide covers the principles of effective policy writing, provides templates for common use cases, and explains how your policy language influences engine selection.

What Makes a Good Policy

Good policies share four characteristics:

Characteristic	Description
Specific	States exactly what fields to check and what documents to expect
Structured	Uses numbered steps that follow a logical verification order
Decisive	Defines clear approve/reject/flag criteria
Complete	Covers all checks your manual process would perform

Omni’s NLP Workflow Generator parses your policy to determine which engines to activate and how to orchestrate them. The more precise your language, the more accurate the engine selection and execution.

Policy Structure Template

Every policy should follow this four-part structure:

[Objective]
Verify the submitted [document type(s)] for [purpose].

[Input Documents]
Expected documents: [list of document types]

[Verification Steps]
1. Extract [specific fields] from [specific document]
2. Verify that [condition A]
3. Check that [condition B]
4. Cross-validate [field X] against [field Y]
5. Screen [person/entity name] against [database/list]

[Decision Criteria]
- APPROVE if [all success conditions]
- REJECT if [any failure conditions]
- FLAG for manual review if [ambiguous conditions]

You do not need to use these exact section headers. What matters is that your policy covers all four areas: objective, inputs, steps, and decisions. Omni parses the meaning, not the formatting.

Examples by Use Case

KYB Business Registration Verification

Verify the submitted business registration documents for corporate entity validation.

Expected documents: business registration certificate, corporate registry extract

Verification steps:
1. Extract company name, registration number, incorporation date, registered address,
   and representative name from the business registration certificate
2. If a corporate registry extract is provided, cross-validate company name and
   registration number between both documents
3. Verify that the incorporation date is in the past and the registration has not expired
4. Check that the registered address includes street, city, and country
5. Screen the representative name against AML/sanctions watchlists
6. Verify that all required fields are present and non-empty

Decision criteria:
- APPROVE if all fields are consistent across documents, no AML matches found,
  and registration is valid and not expired
- REJECT if AML screening returns a high-risk match (SAN-CURRENT, PEP-CURRENT)
  or the registration is expired
- FLAG for manual review if AML returns a partial or medium-risk match,
  or if fields are inconsistent between documents

Engines activated: Text Verifier, AML Search - Person

Invoice Verification

Verify the submitted invoice for payment processing approval.

Expected documents: invoice (PDF or image)

Verification steps:
1. Extract vendor name, vendor address, invoice number, invoice date, payment due date,
   line items (description, quantity, unit price, amount), subtotal, tax amount,
   and total amount
2. Verify that all required fields are present: vendor name, invoice number,
   invoice date, at least one line item, and total amount
3. Calculate the expected subtotal from line items (quantity x unit price for each)
   and check it matches the stated subtotal
4. Verify that tax is calculated correctly based on the subtotal
5. Check that the total equals subtotal plus tax
6. Validate that the invoice date is not in the future
7. Validate that the payment due date is after the invoice date

Decision criteria:
- APPROVE if all required fields are present, all calculations are correct,
  and dates are valid
- REJECT if required fields are missing, amounts do not add up,
  or the invoice date is in the future
- FLAG for manual review if minor discrepancies exist (e.g., rounding differences
  less than 1%) or if any field is partially unreadable

Engines activated: Text Verifier

Compliance Document Check

Review the submitted compliance document to verify regulatory requirements are met.

Expected documents: regulatory license, compliance certificate, or permit document

Verification steps:
1. Extract document type, issuing authority, issue date, expiration date,
   license/permit number, entity name, and scope of authorization
2. Verify that all required sections are present: document header with issuing authority,
   body with license details, signature block, and date fields
3. Check that the expiration date is in the future (document is currently valid)
4. Verify that the entity name on the document matches the expected entity name
5. Confirm that the license/permit number follows the expected format
6. Check that the issuing authority is a recognized regulatory body

Decision criteria:
- APPROVE if all required sections are present, the document is not expired,
  entity names match, and the license number format is valid
- REJECT if the document is expired, required sections are missing,
  or entity names do not match
- FLAG for manual review if the entity name is a close but not exact match,
  or if the issuing authority cannot be verified

Engines activated: Text Verifier

AML Screening with Document Extraction

Screen individuals referenced in the submitted documents against AML/sanctions databases.

Expected documents: any document containing person names (contracts, corporate filings,
partnership agreements, board resolutions)

Verification steps:
1. Extract all person names mentioned in the submitted documents, along with any
   available identifying information (date of birth, nationality, role/title)
2. For each extracted person, perform AML/sanctions watchlist screening
3. Classify screening results by risk level:
   - High risk: current sanctions (SAN-CURRENT), current PEP (PEP-CURRENT),
     regulatory enforcement (REL)
   - Medium risk: linked to PEP (PEP-LINKED), former PEP (PEP-FORMER),
     former sanctions (SAN-FORMER)
   - Low risk: media reports (RRE), insolvency (INS)
4. Summarize all screening results with person name, match status, and risk level

Decision criteria:
- APPROVE if no AML/sanctions matches are found for any screened individual
- REJECT if any individual has a high-risk match
- FLAG for manual review if any individual has a medium-risk or low-risk match

Engines activated: Text Verifier (for name extraction), AML Search - Person (for screening)

Common Mistakes

Avoid these pitfalls when writing policies:

Too vague: 'Verify the document'

Problem: Omni does not know what to verify. “Verify the document” gives no information about which fields to check or what constitutes a pass.Fix: Be explicit about what to check.

# Bad
Verify the document and check if it is valid.

# Good
Extract the company name, registration number, and incorporation date from the
business registration certificate. Verify that all fields are present, the
registration number follows a valid format, and the incorporation date is in the past.

Missing decision criteria

Problem: Without clear approve/reject rules, the AI agent has to guess what constitutes a passing result.Fix: Always end your policy with explicit decision criteria.

# Bad
Extract invoice details and check the amounts.

# Good
Extract invoice details and check the amounts.
- APPROVE if all line item amounts sum to the stated total and all required fields
  are present
- REJECT if amounts do not match or required fields are missing
- FLAG for manual review if amounts match but optional fields are missing

Not mentioning document types

Problem: Omni performs better when it knows what type of document to expect. Without this context, extraction accuracy can suffer.Fix: Specify expected document types at the beginning of your policy.

# Bad
Check the submitted files for compliance.

# Good
Review the submitted business registration certificate (PDF or scanned image)
for corporate compliance requirements.

Over-complex single policy

Problem: Putting too many unrelated verification tasks into one policy makes it hard for the AI agent to execute cleanly. Results become less reliable.Fix: If your process involves fundamentally different types of checks (e.g., invoice validation AND employee background screening), split them into separate workflows.

# Bad - one policy doing everything
Verify the vendor invoice, check the vendor's business registration,
screen all directors against AML lists, validate the vendor's insurance
certificate, and confirm their bank account details.

# Good - split into focused workflows
Workflow 1 (Invoice): Verify invoice amounts, dates, and required fields
Workflow 2 (Vendor KYB): Validate business registration and screen directors
Workflow 3 (Vendor Compliance): Check insurance certificate and bank details

Your wording decides the engines

Which engines get assigned depends on the wording of your policy. When you need a particular check, state that action explicitly in the policy.

Check you need	What to write in the policy	Engine assigned
Extract values from a document	”Extract the legal name and state file number from …”	Text Verifier
Compare values across documents	”The account holder on … must match the legal name on …”	Text Verifier
Check that required items are present	”All three documents must be submitted”	Text Verifier
Screen a person against sanctions	”Screen the managing member’s name against AML and sanctions lists”	AML Search - Person
Screen a company against sanctions	”Screen the legal entity name against AML and sanctions lists”	AML - Business
Look up a Korean business registration	”Look up the registration status by business registration number”	Business Registration Status Check - KOR
Cross-check Korean business details	”Cross-check the company name and representative by business registration number”	Business Info Verification - KOR
Look up a Korean account holder	”Look up the account holder by account number”	Bank Account Owner Name Lookup - KOR
Confirm an address is real	”Validate that the registered address is a real address”	Address Validation

External lookup engines cost credits per call. Do not reach for an external lookup for something you can settle by comparing within the documents. Engine capabilities, prices, and supported countries are in AI model and engines.

One policy can call several engines. To see which engine actually landed on which action, check the playbook action list on the completion screen; if it is not what you wanted, change it in the step engine editor in editing a workflow.

Getting Started

Workflow Templates (Coming soon)

What Makes a Good Policy

Policy Structure Template

Examples by Use Case

Common Mistakes

Your wording decides the engines

What’s Next?

Creating a Workflow

Workflow Templates

​What Makes a Good Policy

​Policy Structure Template

​Examples by Use Case

​Common Mistakes

​Your wording decides the engines

​What’s Next?

Creating a Workflow

Workflow Templates

What Makes a Good Policy

Policy Structure Template

Examples by Use Case

Common Mistakes

Your wording decides the engines

What’s Next?