ShedBoxAI for Fintech

data_sources:
  transactions:
    type: rest
    url: "https://api.stripe.com/v1/charges"
    headers:
      Authorization: "Bearer ${STRIPE_SECRET_KEY}"
    response_path: "data"

processing:
  contextual_filtering:
    transactions:
      - field: "status"
        condition: "succeeded"
        new_name: "successful_transactions"

  advanced_operations:
    monthly_summary:
      source: "successful_transactions"
      group_by: "customer"
      aggregate:
        total_volume: "SUM(amount)"
        transaction_count: "COUNT(*)"
        avg_transaction: "AVG(amount)"
      sort: "-total_volume"

output:
  type: file
  path: "transaction_summary.json"
  format: json

data_sources:
  transactions:
    type: csv
    path: "daily_transactions.csv"

ai_interface:
  model:
    type: rest
    url: "https://api.anthropic.com/v1/messages"
    method: POST
    headers:
      x-api-key: "${ANTHROPIC_API_KEY}"
      Content-Type: "application/json"
    options:
      model: "claude-sonnet-4-20250514"

  prompts:
    detect_anomalies:
      system: "You are a fraud detection analyst."
      user_template: |
        Analyze these transactions for anomalies:

        {% for tx in transactions %}
        - {{ tx.timestamp }}: ${{ tx.amount }} from {{ tx.source }} to {{ tx.destination }}
        {% endfor %}

        Flag any suspicious patterns and explain why.

output:
  type: file
  path: "anomaly_report.md"
  format: json

data_sources:
  revenue:
    type: csv
    path: "revenue.csv"

  expenses:
    type: csv
    path: "expenses.csv"

processing:
  content_summarization:
    revenue:
      method: "statistical"
      fields: ["amount"]
      summarize: ["sum", "count", "mean"]

  content_summarization:
    expenses:
      method: "statistical"
      fields: ["amount"]
      summarize: ["sum", "count", "mean"]

ai_interface:
  model:
    type: rest
    url: "https://api.anthropic.com/v1/messages"
    method: POST
    headers:
      x-api-key: "${ANTHROPIC_API_KEY}"
      Content-Type: "application/json"
    options:
      model: "claude-sonnet-4-20250514"

  prompts:
    report:
      system: "You are a financial analyst."
      user_template: |
        Generate a financial summary based on this data:

        Revenue:
        {% for item in revenue %}
        - {{ item.category }}: ${{ item.amount }}
        {% endfor %}

        Expenses:
        {% for item in expenses %}
        - {{ item.category }}: ${{ item.amount }}
        {% endfor %}

        Provide insights and recommendations.

output:
  type: file
  path: "monthly_report.md"
  format: json