Compliance annotation. Built for fintech.

# POST /api/annotate — classify transaction narrative for SAR review
curl -X POST https://tagmatic.app/api/annotate \
  -H "X-API-Key: tmk_your_key" \
  -H "Content-Type: application/json" \
  -d '{
    "text": "Customer deposited $9,500 cash across 3 branches within 24 hours.",
    "schema": [
      { "name": "sar_required", "type": "classification",
        "values": ["requires_SAR", "suspicious_activity", "routine"] },
      { "name": "structuring_detected", "type": "boolean",
        "description": "Pattern suggests structuring to avoid CTR threshold" },
      { "name": "risk_indicators", "type": "span",
        "description": "Phrases indicating suspicious activity", "multi": true }
    ],
    "guidelines": "Apply BSA/AML standards. Flag structuring patterns."
  }'

# Response body — low confidence auto-routes to compliance review queue
{
  "annotations": [
    { "label": "sar_required", "value": "requires_SAR",
      "confidence": 0.96, "needs_review": false },
    { "label": "structuring_detected", "value": true,
      "confidence": 0.94, "needs_review": false },
    { "label": "risk_indicators", "value": "$9,500 cash across 3 branches",
      "start": 19, "end": 50, "confidence": 0.98, "needs_review": false }
  ],
  "summary": { "total": 3, "flagged_for_review": 0 }
}

import requests

result = requests.post(
    "https://tagmatic.app/api/annotate",
    headers={"X-API-Key": "tmk_your_key"},
    json={
        "text": "Beneficial owner: John Smith, DOB: 03/15/1982, Passport: US12345678. UBO holds 35% equity in Acme Holdings Ltd, registered in Delaware.",
        "schema": [
            {"name": "person_names", "type": "span", "description": "Individual names", "multi": True},
            {"name": "id_documents", "type": "span", "description": "Passport, SSN, or ID numbers", "multi": True},
            {"name": "ownership_pct", "type": "span", "description": "Ownership percentages", "multi": True},
            {"name": "ubo_threshold_met", "type": "boolean", "description": "UBO ownership exceeds 25% CDD threshold"},
        ],
    },
).json()

for ann in result["annotations"]:
    if ann["needs_review"]:
        route_to_kyc_analyst(ann)   # low-confidence → human review
    else:
        save_to_kyc_record(ann)     # auto-approved, timestamped

import requests

# POST /api/annotate/batch — screen multiple records for PII exposure
response = requests.post(
    "https://tagmatic.app/api/annotate/batch",
    headers={"X-API-Key": "tmk_your_key"},
    json={
        "texts": [
            "Account holder email: jane@example.com, SSN ending 4532.",
            "Wire transfer $45,000 to high-risk jurisdiction, no prior relationship.",
            "Routine payroll deposit from verified employer, monthly cadence."
        ],
        "schema": [
            {"name": "contains_pii", "type": "boolean",
             "description": "Text contains PII (email, SSN, passport, DOB)"},
            {"name": "aml_risk", "type": "classification",
             "values": ["high", "medium", "low"]}
        ],
        # POST results to your AML case management system
        "callback_url": "https://your-aml-platform.com/webhooks/tagmatic"
    }
)

data = response.json()
# → { "job_id": "job_abc123", "status": "queued", "count": 3 }
# Tagmatic POSTs to callback_url when done:
# { "job_id": "job_abc123", "status": "done",
#   "summary": { "total": 3, "flagged_for_review": 1 },
#   "results": [{ "text": "...", "annotations": [...] }] }
print(data["job_id"])  # or poll GET /api/batch/{job_id}