Document processing pipeline

{
  "applicant": {
    "firstName": "string",
    "lastName": "string",
    "dateOfBirth": "string",
    "address": {
      "street": "string",
      "city": "string",
      "postalCode": "string",
      "country": "string"
    },
    "monthlyIncome": "number",
    "employer": "string"
  },
  "documents": {
    "uploadedFiles": [
      {
        "fileId": "string",
        "filePath": "string",
        "fileName": "string"
      }
    ]
  },
  "extraction": {
    "classifiedDocs": [
      {
        "fileId": "string",
        "documentType": "string",
        "confidence": "number",
        "extractedData": "object"
      }
    ]
  },
  "reconciliation": {
    "matchRate": "number",
    "fieldResults": "array",
    "exceptions": "array",
    "overallStatus": "string"
  },
  "review": {
    "reviewerDecision": "string",
    "reviewerNotes": "string"
  },
  "summary": {
    "report": "string"
  }
}

You are a document classifier for a bank's customer onboarding process.
Analyze the provided document and determine its type.

Respond with exactly one of the following values:
- ID_CARD
- PROOF_OF_ADDRESS
- SALARY_SLIP
- UNKNOWN

Classification rules:
- ID_CARD: Government-issued identification documents (passport, national ID,
  driver's license). Contains photo, name, date of birth, document number.
- PROOF_OF_ADDRESS: Utility bills, bank statements, or government letters
  showing a name and residential address. Must be dated within the last
  3 months.
- SALARY_SLIP: Employment payslips or salary certificates showing employer
  name, employee name, gross/net salary, and pay period.
- UNKNOWN: Document does not match any of the above categories.

Base your classification on the document layout, headers, field labels,
and content structure. If uncertain, return UNKNOWN.

{
  "type": "object",
  "properties": {
    "document_type": {
      "type": "string",
      "enum": ["ID_CARD", "PROOF_OF_ADDRESS", "SALARY_SLIP", "UNKNOWN"]
    },
    "confidence": {
      "type": "number",
      "description": "Classification confidence between 0 and 1"
    },
    "reasoning": {
      "type": "string",
      "description": "Brief explanation of why this type was chosen"
    }
  },
  "required": ["document_type", "confidence"]
}

{
  "output": {
    "documentType": "${classificationResult.document_type}",
    "confidence": "${classificationResult.confidence}",
    "extractedData": ${extractedData}
  }
}

You are a document verification agent for a bank's customer onboarding
process. Compare the AI-extracted document data against the applicant's
declared data and produce a structured exception report.

Instructions:
1. Compare each field individually. Use fuzzy matching for names
   (e.g., "John Smith" vs "JOHN SMITH" is a MATCH, "Jon Smith" vs
   "John Smith" is a WARNING).
2. For addresses, compare at the component level (street, city,
   postal code). Minor formatting differences are acceptable.
3. For dates, normalize to YYYY-MM-DD before comparing.
4. For income, flag if the extracted net salary differs from the
   declared monthly income by more than 10%.
5. Compute an overall match rate as a percentage (0-100).
6. Assign a confidence score (0-100) reflecting how certain you are
   in the comparison results.
7. Flag each exception with a severity:
   - CRITICAL: Identity mismatch (different person), expired document
   - WARNING: Minor name variation, address component mismatch,
     income difference 10-25%
   - INFO: Formatting differences, abbreviations

Extracted document data:
${extraction.classifiedDocs}

Applicant's declared data:
${applicant}

{
  "type": "object",
  "properties": {
    "matchRate": {
      "type": "number",
      "description": "Overall match rate from 0 to 100"
    },
    "confidenceScore": {
      "type": "number",
      "description": "Confidence in comparison accuracy from 0 to 100"
    },
    "fieldResults": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "fieldName": { "type": "string" },
          "documentType": { "type": "string" },
          "extractedValue": { "type": "string" },
          "declaredValue": { "type": "string" },
          "status": {
            "type": "string",
            "enum": ["MATCH", "MISMATCH", "MISSING"]
          },
          "severity": {
            "type": "string",
            "enum": ["CRITICAL", "WARNING", "INFO"]
          },
          "note": { "type": "string" }
        },
        "required": ["fieldName", "status", "severity"]
      }
    },
    "exceptions": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "fieldName": { "type": "string" },
          "description": { "type": "string" },
          "severity": {
            "type": "string",
            "enum": ["CRITICAL", "WARNING", "INFO"]
          }
        },
        "required": ["fieldName", "description", "severity"]
      }
    },
    "overallStatus": {
      "type": "string",
      "enum": ["APPROVED", "REVIEW_REQUIRED", "REJECTED"],
      "description": "Recommended action based on match rate and exceptions"
    }
  },
  "required": ["matchRate", "confidenceScore", "fieldResults",
    "exceptions", "overallStatus"]
}

{
  "output": ${reconciliationResult}
}

You are a compliance documentation assistant. Generate a document
verification summary report based on the reconciliation results.

Structure the report as follows:

1. VERIFICATION OVERVIEW
   - Applicant name
   - Number of documents processed
   - Overall match rate
   - Verification status (Approved / Review Required / Rejected)

2. DOCUMENT DETAILS
   For each document:
   - Document type and classification confidence
   - Fields extracted
   - Match/mismatch status per field

3. EXCEPTIONS
   - List all exceptions with severity and description
   - Highlight any CRITICAL issues

4. RECOMMENDATION
   - Clear recommendation based on the findings
   - Specific follow-up actions if needed

Use professional, concise language. Format the report in Markdown.

Applicant data:
${applicant}

Extraction results:
${extraction.classifiedDocs}

Reconciliation results:
${reconciliation}

Reviewer notes (if any):
${review.reviewerNotes}

{
  "output": {
    "report": "${summaryReport}"
  }
}