DeepRead Insurance Documents

Extract structured data from insurance claims, policies, EOBs, and loss reports. Pre-built schemas for claimant info, coverage, damages, adjuster notes. PII...

Security Scan

The skill is internally consistent with its stated purpose — it only needs a DeepRead API key and instructs the agent to POST documents to DeepRead's API — but you should review how and when PII is uploaded and retained by the service before using it with real claims data.

Purpose & Capability

Name/description (insurance document extraction + PII redaction) matches what the SKILL.md instructs: POST documents to https://api.deepread.tech, poll for results, and return structured JSON. Required env var is a single DEEPREAD_API_KEY which is appropriate for this external API.

Instruction Scope

Instructions are narrowly scoped to submitting documents to the DeepRead API and retrieving structured results. However, the doc promises 'PII redaction for compliant sharing' but does not make clear whether redaction happens locally before upload or on DeepRead's servers after processing; the instructions show uploading entire documents to the remote API, meaning PII will be sent to the third party unless you locally redact first.

Install Mechanism

No install spec and no bundled code — instruction-only skill. Nothing is written to disk by an installer in this bundle.

Credentials

Only requests a single API key (DEEPREAD_API_KEY) as the primary credential, which is proportional and expected for a hosted OCR/ML extraction service. No unrelated credentials or config paths are requested.

Persistence & Privilege

Skill is not always-enabled, is user-invocable, and does not request modification of other skills or system settings. It does not demand persistent privileges beyond the supplied API key.

Assessment

This skill appears to do what it claims, but it sends documents to a third-party API. Before using with real insurance claims or other sensitive PII: 1) Verify DeepRead's privacy, retention, and data processing terms (DPA/GDPR/HIPAA if applicable). 2) Confirm whether redaction occurs server-side and whether you should redact/sanitize locally before upload. 3) Use a scoped/rotatable API key and avoid uploading unnecessary data for testing. 4) Ensure uploads use TLS (the SKILL.md uses https://api.deepread.tech). 5) If your organization requires on-prem or customer-controlled processing, confirm the vendor supports that. If any of these points are unresolved, treat the skill as higher risk and avoid sending production PII until clarified.

DeepRead Insurance Document Processing

Extract structured data from insurance claims, policy documents, Explanations of Benefits (EOBs), loss reports, and adjuster notes. Then redact claimant PII before sharing with third parties.

This skill instructs the agent to POST documents to https://api.deepread.tech and poll for results. No system files are modified.

What You Get Back

Submit a claim form and get structured JSON:

{
  "claim_number": {"value": "CLM-2026-078432", "hil_flag": false, "found_on_page": 1},
  "policy_number": {"value": "POL-HO3-445521", "hil_flag": false, "found_on_page": 1},
  "claimant_name": {"value": "Robert Johnson", "hil_flag": false, "found_on_page": 1},
  "date_of_loss": {"value": "2026-02-14", "hil_flag": false, "found_on_page": 1},
  "date_reported": {"value": "2026-02-15", "hil_flag": false, "found_on_page": 1},
  "loss_type": {"value": "Water Damage", "hil_flag": false, "found_on_page": 1},
  "loss_description": {"value": "Burst pipe in basement caused flooding to finished living area, damaged drywall, carpet, and personal property", "hil_flag": false, "found_on_page": 2},
  "property_address": {"value": "789 Elm Dr, Denver, CO 80202", "hil_flag": false, "found_on_page": 1},
  "coverage_type": {"value": "Homeowners HO-3", "hil_flag": false, "found_on_page": 1},
  "deductible": {"value": 1000.00, "hil_flag": false, "found_on_page": 1},
  "estimated_damages": {"value": 24500.00, "hil_flag": true, "reason": "Multiple estimates on different pages"},
  "adjuster": {"value": "Sarah Martinez, License #ADJ-44521", "hil_flag": false, "found_on_page": 3},
  "line_items": {"value": [
    {"category": "Structural", "description": "Drywall replacement — basement", "amount": 8500.00},
    {"category": "Flooring", "description": "Carpet removal and replacement", "amount": 6200.00},
    {"category": "Personal Property", "description": "Damaged furniture and electronics", "amount": 5800.00},
    {"category": "Mitigation", "description": "Water extraction and drying", "amount": 4000.00}
  ], "hil_flag": false, "found_on_page": 3},
  "status": {"value": "Under Review", "hil_flag": false, "found_on_page": 1}
}

Fields with hil_flag: true need human review. Everything else is high-confidence.

Setup

Get Your API Key

open "https://www.deepread.tech/dashboard/?utm_source=clawhub"

Save it:

export DEEPREAD_API_KEY="sk_live_your_key_here"

Insurance Claim Schema

Pre-built schema for insurance claims and loss reports:

{
  "type": "object",
  "properties": {
    "claim_number": {"type": "string", "description": "Claim number or reference ID"},
    "policy_number": {"type": "string", "description": "Insurance policy number"},
    "claimant_name": {"type": "string", "description": "Name of the claimant or insured"},
    "date_of_loss": {"type": "string", "description": "Date the loss or incident occurred (YYYY-MM-DD)"},
    "date_reported": {"type": "string", "description": "Date the claim was reported (YYYY-MM-DD)"},
    "loss_type": {"type": "string", "description": "Type of loss (Water Damage, Fire, Theft, Auto Collision, Liability, etc.)"},
    "loss_description": {"type": "string", "description": "Detailed description of the loss or incident"},
    "property_address": {"type": "string", "description": "Address of the property or location of incident"},
    "coverage_type": {"type": "string", "description": "Type of coverage (Homeowners, Auto, Commercial, Liability, etc.)"},
    "deductible": {"type": "number", "description": "Policy deductible amount"},
    "estimated_damages": {"type": "number", "description": "Total estimated damage amount"},
    "adjuster": {"type": "string", "description": "Claims adjuster name and license number"},
    "line_items": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "category": {"type": "string", "description": "Damage category (Structural, Personal Property, Medical, etc.)"},
          "description": {"type": "string", "description": "Description of damage or expense"},
          "amount": {"type": "number", "description": "Cost or estimate amount"}
        }
      },
      "description": "Itemized list of damages or expenses"
    },
    "status": {"type": "string", "description": "Claim status (Filed, Under Review, Approved, Denied, Settled)"},
    "settlement_amount": {"type": "number", "description": "Final settlement amount if resolved"},
    "denial_reason": {"type": "string", "description": "Reason for denial if applicable"}
  }
}

Extract Data From Insurance Documents

Python

import requests
import json
import time

API_KEY = "sk_live_YOUR_KEY"
BASE = "https://api.deepread.tech"
headers = {"X-API-Key": API_KEY}

schema = json.dumps({
    "type": "object",
    "properties": {
        "claim_number": {"type": "string", "description": "Claim number"},
        "policy_number": {"type": "string", "description": "Policy number"},
        "claimant_name": {"type": "string", "description": "Claimant name"},
        "date_of_loss": {"type": "string", "description": "Date of loss (YYYY-MM-DD)"},
        "loss_type": {"type": "string", "description": "Type of loss"},
        "loss_description": {"type": "string", "description": "Description of the loss"},
        "coverage_type": {"type": "string", "description": "Coverage type"},
        "deductible": {"type": "number", "description": "Deductible amount"},
        "estimated_damages": {"type": "number", "description": "Total estimated damages"},
        "line_items": {
            "type": "array",
            "items": {"type": "object", "properties": {
                "category": {"type": "string"},
                "description": {"type": "string"},
                "amount": {"type": "number"}
            }},
            "description": "Itemized damages"
        },
        "status": {"type": "string", "description": "Claim status"}
    }
})

with open("claim.pdf", "rb") as f:
    job = requests.post(
        f"{BASE}/v1/process",
        headers=headers,
        files={"file": f},
        data={"schema": schema},
    ).json()

job_id = job["id"]
print(f"Processing: {job_id}")

delay = 5
while True:
    time.sleep(delay)
    result = requests.get(f"{BASE}/v1/jobs/{job_id}", headers=headers).json()

    if result["status"] == "completed":
        data = result["result"]["data"]
        print(json.dumps(data, indent=2))

        for field, value in data.items():
            if isinstance(value, dict) and value.get("hil_flag"):
                print(f"\n  REVIEW: {field} — {value.get('reason')}")
        break
    elif result["status"] == "failed":
        print(f"Failed: {result.get('error')}")
        break

    delay = min(delay * 1.5, 15)

cURL

curl -s -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@claim.pdf" \
  -F 'schema={"type":"object","properties":{"claim_number":{"type":"string","description":"Claim number"},"policy_number":{"type":"string","description":"Policy number"},"claimant_name":{"type":"string","description":"Claimant name"},"date_of_loss":{"type":"string","description":"Date of loss"},"loss_type":{"type":"string","description":"Type of loss"},"estimated_damages":{"type":"number","description":"Total damages"},"status":{"type":"string","description":"Claim status"}}}'

Redact Claimant PII Before Sharing

Redact claimant personal information before sending to adjusters, contractors, or third-party reviewers:

# Step 1: Extract the claim data you need
with open("claim.pdf", "rb") as f:
    extract_job = requests.post(
        f"{BASE}/v1/process",
        headers=headers,
        files={"file": f},
        data={"schema": schema},
    ).json()

# Step 2: Redact PII from the original
with open("claim.pdf", "rb") as f:
    redact_job = requests.post(
        f"{BASE}/v1/pii/redact",
        headers=headers,
        files={"file": f},
    ).json()

redact_id = redact_job["id"]
delay = 5
while True:
    time.sleep(delay)
    result = requests.get(f"{BASE}/v1/pii/{redact_id}", headers=headers).json()
    if result["status"] == "completed":
        report = result["report"]
        print(f"Redacted {report['total_redactions']} PII instances")
        for pii_type, info in report["pii_detected"].items():
            print(f"  {pii_type}: {info['count']} found")
        pdf = requests.get(result["redacted_file_url"]).content
        with open("claim_redacted.pdf", "wb") as f:
            f.write(pdf)
        print("Saved: claim_redacted.pdf")
        break
    elif result["status"] == "failed":
        print(f"Failed: {result.get('error')}")
        break
    delay = min(delay * 1.5, 15)

Use Cases

• Claims Processing — Extract claim numbers, dates, damage descriptions, and amounts from incoming claims
• Policy Document Analysis — Pull coverage terms, limits, deductibles, and exclusions from policy documents
• EOB Processing — Extract procedure codes, allowed amounts, patient responsibility from Explanations of Benefits
• Loss Reports — Parse adjuster field reports for damage categories, estimates, and recommendations
• Subrogation — Extract third-party liability information and recovery amounts
• Fraud Detection — Batch-process claims and flag inconsistencies in dates, amounts, or descriptions
• Auto Claims — Extract vehicle info, driver details, accident descriptions, and repair estimates
• Workers Comp — Pull injury descriptions, medical provider info, and lost wage calculations

Tips for Insurance Documents

• Specify claim-specific field names — Using "Claim number or reference ID" works better than just "number"
• Include status values — Adding expected statuses (Filed, Under Review, Approved, Denied) in descriptions helps extraction
• Create blueprints for recurring form types — If you process the same carrier's claim forms repeatedly, train a blueprint at deepread.tech/dashboard/optimizer for 20-30% improvement
• Always redact before external sharing — Use PII redaction before sending to contractors, adjusters, or legal teams

BYOK — Zero Processing Costs

Connect your own OpenAI, Google, or OpenRouter key via the dashboard. All document processing routes through your provider — zero DeepRead LLM costs, page quota skipped.

Set it up: https://www.deepread.tech/dashboard/byok

Related DeepRead Skills

• deepread-ocr — General OCR and structured extraction — clawhub install uday390/deepread-ocr
• deepread-pii — Redact PII from any document — clawhub install uday390/deepread-pii
• deepread-form-fill — Fill PDF forms with AI vision — clawhub install uday390/deepread-form-fill
• deepread-invoice — Invoice and receipt processing — clawhub install uday390/deepread-invoice
• deepread-medical — Medical records processing — clawhub install uday390/deepread-medical
• deepread-legal — Legal document processing — clawhub install uday390/deepread-legal
• deepread-agent-setup — OAuth device flow authentication — clawhub install uday390/deepread-agent-setup
• deepread-byok — Bring Your Own Key setup — clawhub install uday390/deepread-byok

Support

• Dashboard: https://www.deepread.tech/dashboard
• Demo Repo: https://github.com/deepread-tech/deepread-demo
• n8n Node: https://www.npmjs.com/package/n8n-nodes-deepread
• Issues: https://github.com/deepread-tech/deep-read-service/issues
• Email: [e-mail]

---

Get started free: https://www.deepread.tech/dashboard/?utm_source=clawhub