Transform Blocks

Overview

Transform blocks are the processing layer of a workflow. They define how data or documents are transformed, categorized, routed, or enriched before being passed on to the next step.

These blocks can perform AI-based classification, conditional routing, or manual intervention when needed.

Configuring Transform Blocks

Below are the available configuration options and example setups for each Transform Block.

Data Extraction Block

Configuration Steps:

1. Select Document Type: Choose the document type from the dropdown (e.g., US Bank Statement).

2. Run Test: Click Test Block to extract data and view the JSON output.

3. Review Output: Switch between JSON and Table view to verify extracted fields.

   

Example Use Case:
Extract bank details from uploaded statements:

{
  "account_name": "John Doe",
  "bank_name": "Chase Bank",
  "transactions": [...]
}

Merge JSON Block

Configuration Steps:

1. Review Output: Test the merged output to ensure data structure integrity.

Categorize with AI Block

Configuration Steps:

1. Describe Categorization Rules: Define the logic for how AI should categorize data (e.g., loan type, borrower risk, or document class).

2. Import Categories: Optionally, import from an existing table and select relevant columns.

3. Test: Click Test Block to preview AI-generated categories.

   

Example Use Case (SMB Lending):

Automatically categorize loan applications based on business type and risk profile:

Document Type Classifier Block

Configuration Steps:

1. Select Document Type: Choose the category or list of document types that the model should classify.
2. Advanced option: Provide instructions to the model on how to classify the documents
3. Review Classification: Validate predicted results before proceeding.

Example Use Case:

Automatically classify uploaded files into:

• Bank Statement
• Invoice
• Pay Slip

Python Code Block

Configuration Steps:

1. Define Function Logic: Use the prompt input to automatically generate validation or transformation code, or manually write your own Python function inside the editor.
2. Review and Edit: Modify the generated code as needed — for example, add conditional checks or data manipulations.
3. Test Execution: Click Test Block to validate the output with sample input data.

Example Use Case (SMB Lending):

Use Python to validate uploaded loan documents. This example verifies that the uploaded files contain bank statements before sending them for further processing.

def execute(data):
    # Example: Validate if uploaded documents contain 'bank statement'
    valid_docs = []
    for doc in data.get("documents", []):
        if "bank statement" in doc["name"].lower():
            valid_docs.append(doc)
    return {"valid_documents": valid_docs, "total_valid": len(valid_docs)}

 

Human in the Loop Block

Configuration Steps:

1. Select One or More Users: Choose the users who will review or approve the data output from previous blocks.

2. Select Assignment Mode: Decide how the task should be assigned — for example,

   • Round Robin Broadcast – Tasks are assigned evenly among selected users in rotation.
     (Useful for balancing workload across a review team.)
   • Sequential Broadcast – Tasks are assigned one user at a time based on priority order.
     (Useful for hierarchical review or escalation flows.)

3. Advanced Options:

   • Notify Users: Enable to send email notifications to assigned reviewers.
   • Rejection Reason Required: Require reviewers to provide a reason when rejecting a record.

4. Test Block:
   Click Test Block to simulate the review workflow and ensure assignments work as expected.

   

Example Use Case (SMB Lending):

After documents are automatically classified and extracted, send records with low confidence scores to a credit analyst for manual review.

Router Block

Configuration Steps

1. Define Routing Logic

   • In the File Filters section, describe the logic for how documents should be routed.
   • Example:

     IF → Credit Score >= 700 AND Average Monthly Balance > $10,000  
     ELSE IF → Credit Score between 650 and 699 AND No NSF (Non-Sufficient Funds) in last 6 months  
     ELSE IF → Credit Score < 650 OR NSF Count > 3 in last 6 months  
     ELSE → Any other case not matching above
     

2. Generate Routing Conditions

   • Click Generate Routing Conditions to automatically create routes for each logic branch.
   • Each route can lead to a different step (e.g., verification, AI categorization, or human review).

3. Set Condition Rules: Use logical operators to define rules precisely:

   • ALL → all sub-conditions must be true.
   • ANY → at least one sub-condition must be true.

4. Else Condition Handles any document that doesn’t meet the specified routing criteria.

   • Default value is Unclassified, but you can rename it.

5. Test Block: Click Test Block to preview routing results using sample data.

   

Example Use Case: SMB Loan Application Routing