DeepRead PII Redaction

Data & APIs

Redact 14 types of PII from PDFs, images, and text using context-aware AI that removes data irreversibly with black bars, supporting multi-language and audit...

Install

openclaw skills install deepread-pii

DeepRead PII — Document Redaction API

Your agent processes documents. Some of those documents contain names, SSNs, medical records, credit card numbers. Before that data flows to another API, a database, a teammate, or an LLM — it needs to be clean.

Input:  "Invoice to: John Smith, 123 Oak St, SSN: 456-78-9012, Card: 4532-1234-5678-9012"
Output: "Invoice to: ██████████, ██████████, SSN: ███████████, Card: ███████████████████"

One API call. Document in, redacted copy + detection report back.

DeepRead PII detects 14 types of personally identifiable information using context-aware AI — not regex. It knows "Dr. Sarah Chen" on a hospital letterhead is the physician (skip), but "Sarah Chen" on a patient intake form is the patient (redact). No regex rules to write. No word lists to maintain. No false positive floods.

This skill instructs the agent to POST your file to https://api.deepread.tech, poll for results, and download the redacted copy. No system files are modified and no elevated permissions are requested.

What This Skill Does

14 PII types detected: Names, SSNs, credit cards, emails, phones, addresses, dates of birth, passport numbers, driver's licenses, bank accounts, IBANs, IPs, URLs, medical record numbers
Black bar redaction: PII replaced with solid black bars — text physically removed from the PDF content stream, irreversible, not just a visual overlay
Any document format: PDF (digital + scanned), PNG, JPEG, plain text
Context-aware: AI distinguishes personal vs. institutional, patient vs. provider, form labels vs. actual values
Audit trail: Every redaction logged with detection counts per type. See DeepRead's privacy policy for data handling details.
Copy-paste proof: Redacted text cannot be recovered via copy-paste, text selection, or PDF parsing
Free tier: 2,000 pages/month (no credit card required)
Works with other DeepRead skills: Extract data with deepread-ocr, fill forms with deepread-form-fill, then redact the originals

Setup

1. Get Your API Key

# Visit the dashboard
https://www.deepread.tech/dashboard

# Or use this direct link
https://www.deepread.tech/dashboard/?utm_source=clawhub

Save your API key:

export DEEPREAD_API_KEY="sk_live_your_key_here"

2. Configuration (Optional)

Add to your clawdbot.config.json5:

{
  skills: {
    entries: {
      "deepread-pii": {
        enabled: true
        // API key is read from DEEPREAD_API_KEY environment variable
        // Do NOT hardcode your API key here
      }
    }
  }
}

3. Redact Your First Document

Option A: With Webhook (Recommended)

curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@document.pdf" \
  -F "webhook_url=https://your-app.com/webhooks/pii"

# Returns immediately:
{
  "id": "550e8400-e29b-41d4-a716-446655440000",
  "status": "queued"
}

# Your webhook receives results when processing completes

Option B: Poll for Results

curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@patient_record.pdf"

# Returns immediately:
{
  "id": "550e8400-e29b-41d4-a716-446655440000",
  "status": "queued"
}

# Poll until completed:
curl https://api.deepread.tech/v1/pii/550e8400-e29b-41d4-a716-446655440000 \
  -H "X-API-Key: $DEEPREAD_API_KEY"

Usage Examples

Redact a PDF

Replaces all detected PII with solid black bars. Text is physically removed from the PDF content stream. Copy-paste cannot recover it.

curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@contract.pdf"

Response when completed:

{
  "id": "550e8400-...",
  "status": "completed",
  "progress_percent": 100,
  "redacted_file_url": "https://...(signed URL)...",
  "report": {
    "id": "550e8400-...",
    "page_count": 5,
    "processing_time_ms": 3421,
    "pii_detected": {
      "NAME": {
        "count": 3,
        "pages": [1, 2],
        "confidence_avg": 0.92
      },
      "PHONE": {
        "count": 2,
        "pages": [1],
        "confidence_avg": 0.89
      },
      "EMAIL": {
        "count": 1,
        "pages": [2],
        "confidence_avg": 0.97
      }
    },
    "total_redactions": 6,
    "redaction_policy": "black_bar",
    "confidence_threshold_used": 0.85,
    "below_threshold_count": 0
  }
}

Redact an Image

Works on scanned documents, photos of IDs, screenshots — any PNG or JPEG.

curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@drivers_license.png"

Vision AI detects PII in the image, locates exact positions, and draws black bars over the text.

Redact Plain Text

curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@notes.txt"

Before: Patient John Smith, SSN 456-78-9012, called from (555) 867-5309 After: Patient ██████████, SSN ███████████, called from ██████████████

Multi-Language Support

Supports documents in English, Chinese, Spanish, Hindi, and Arabic.

curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@documento.pdf" \
  -F "language=es"

Supported languages: en (default), zh, es, hi, ar

When to Use This Skill

Use DeepRead PII For:

Before sharing documents externally — redact before sending to vendors, partners, opposing counsel
Before feeding documents to LLMs — strip PII before sending content to any AI model
Compliance workflows — GDPR right to erasure, HIPAA de-identification, CCPA requests
Training data preparation — create clean datasets from real documents
Insurance claims — redact claimant PII before adjuster handoff
Legal discovery — privilege review with PII protection
Medical records — de-identify patient data for research or sharing
Financial documents — mask account numbers, SSNs on statements
HR documents — clean employee files before audits

Don't Use For:

Real-time processing — async workflow, not instant (use webhooks)
Structured data extraction — use deepread-ocr skill for that, then redact
Documents with no text — blank images or decorative PDFs

How It Works

3-Layer Detection Pipeline

Document → AI Detection → Threshold Filter → Context Validation → Redact

Layer 1: AI Detection

Text documents: LLM scans for all 14 PII types with confidence scoring
Images/scans: Vision model detects PII with precise bounding box coordinates
Returns type, exact value, and confidence score (0.0–1.0) for each detection

Layer 2: Confidence Threshold

Default threshold: 0.85
Detections below threshold are recorded but NOT redacted
Reported separately as below_threshold_count for manual review

Layer 3: Context-Aware Validation

Second AI pass with full document context
Filters false positives that regex-based tools can't handle:
- admissions@university.edu → institutional email, SKIP
- john.smith@gmail.com → personal email, REDACT
- "Dr. Sarah Chen" on letterhead → physician, SKIP
- "Sarah Chen" on intake form → patient, REDACT
- "Name:" (form label) → not PII, SKIP
- "John Smith" (form value) → PII, REDACT
- Invoice dates → not DOB, SKIP
- "Date of Birth: 03/15/1990" → DOB, REDACT

What Gets Detected

PII Type	Examples
`SSN`	Social Security numbers, national IDs
`CREDIT_CARD`	Card numbers, transaction IDs tied to a person
`EMAIL`	Personal email addresses (not institutional)
`PHONE`	Phone numbers (all country formats)
`NAME`	Person names (all cultures/languages)
`ADDRESS`	Physical addresses, postal codes
`IP_ADDRESS`	IPv4 and IPv6 addresses
`DATE_OF_BIRTH`	Birth dates (only when labeled as DOB — not random dates)
`PASSPORT_NUMBER`	Passport numbers
`DRIVER_LICENSE`	Driver's licenses, registration numbers
`BANK_ACCOUNT`	Account numbers, routing numbers
`IBAN`	International Bank Account Numbers
`URL`	Personal URLs and web addresses
`MEDICAL_RECORD`	Medical record numbers, patient IDs, hospital IDs

PDF Redaction is Irreversible

Digital PDFs: Text is physically removed from the PDF content stream using redaction annotations — not just covered
Scanned PDFs: Pages are re-rendered as images with black bars, replacing the original
All PDFs: Metadata stripped, content streams cleaned and deflated
Copy-paste, text selection, and PDF parsing cannot recover redacted content

API Reference

POST /v1/pii/redact — Submit Document for Redaction

Auth: X-API-Key: YOUR_KEY Content-Type: multipart/form-data Rate Limit: 10 requests per 60 seconds

Parameter	Type	Required	Default	Description
`file`	File	Yes	—	PDF, PNG, JPEG, or TXT (max 50MB)
`language`	string	No	`"en"`	`"en"`, `"zh"`, `"es"`, `"hi"`, `"ar"`
`webhook_url`	string	No	—	HTTPS URL for completion notification

Response (200 OK):

{
  "id": "550e8400-e29b-41d4-a716-446655440000",
  "status": "queued"
}

Errors:

Status	Code	Meaning
400	`INVALID_REQUEST`	Bad request parameters
400	`UNSUPPORTED_FORMAT`	File type not supported
400	`EMPTY_DOCUMENT`	File is empty
400	`DOCUMENT_CORRUPTED`	File is corrupt or unreadable
400	`PASSWORD_PROTECTED`	Document is password-protected
401	`UNAUTHORIZED`	Invalid or missing API key
413	`FILE_TOO_LARGE`	Exceeds 50MB size limit
429	`RATE_LIMITED`	Rate limit exceeded
500	`INTERNAL_ERROR`	Server error (retry or contact support)

GET /v1/pii/{job_id} — Get Redaction Results

Auth: X-API-Key: YOUR_KEY Rate Limit: 60 requests per 60 seconds

Poll until status is completed or failed.

Response (completed):

{
  "id": "550e8400-...",
  "status": "completed",
  "progress_percent": 100,
  "redacted_file_url": "https://...(signed URL)...",
  "report": {
    "id": "550e8400-...",
    "page_count": 3,
    "processing_time_ms": 4200,
    "pii_detected": {
      "NAME": {
        "count": 4,
        "pages": [1, 2, 3],
        "confidence_avg": 0.93,
        "confidence_min": 0.87,
        "below_threshold": 0,
        "allowed": 0
      },
      "SSN": {
        "count": 1,
        "pages": [1],
        "confidence_avg": 0.98,
        "confidence_min": 0.98,
        "below_threshold": 0,
        "allowed": 0
      }
    },
    "total_redactions": 5,
    "redaction_policy": "black_bar",
    "confidence_threshold_used": 0.85,
    "below_threshold_count": 0
  },
  "error": null
}

Response (failed):

{
  "id": "550e8400-...",
  "status": "failed",
  "progress_percent": 0,
  "redacted_file_url": null,
  "report": null,
  "error": {
    "code": "DOCUMENT_CORRUPTED",
    "message": "Unable to process the document"
  }
}

Statuses: queued → processing → completed or failed

Code Examples

Python

import requests
import time

API_KEY = "sk_live_YOUR_KEY"
BASE = "https://api.deepread.tech"

# Submit document for redaction
with open("patient_record.pdf", "rb") as f:
    resp = requests.post(
        f"{BASE}/v1/pii/redact",
        headers={"X-API-Key": API_KEY},
        files={"file": f},
    )
job_id = resp.json()["id"]

# Poll with backoff
delay = 3
while True:
    time.sleep(delay)
    result = requests.get(
        f"{BASE}/v1/pii/{job_id}",
        headers={"X-API-Key": API_KEY}
    ).json()

    if result["status"] == "completed":
        # Download redacted file
        redacted_url = result["redacted_file_url"]
        redacted_pdf = requests.get(redacted_url).content
        with open("patient_record_redacted.pdf", "wb") as f:
            f.write(redacted_pdf)

        # Review detection report
        report = result["report"]
        print(f"Redacted {report['total_redactions']} PII instances")
        for pii_type, summary in report["pii_detected"].items():
            print(f"  {pii_type}: {summary['count']} found on pages {summary['pages']}")
        break

    elif result["status"] == "failed":
        print(f"Failed: {result['error']['message']}")
        break

    delay = min(delay * 1.5, 15)

JavaScript / Node.js

import fs from "fs";

const API_KEY = "sk_live_YOUR_KEY";
const BASE = "https://api.deepread.tech";

// Submit document
const form = new FormData();
form.append("file", fs.createReadStream("contract.pdf"));

const { id: jobId } = await fetch(`${BASE}/v1/pii/redact`, {
  method: "POST",
  headers: { "X-API-Key": API_KEY },
  body: form,
}).then((r) => r.json());

// Poll with backoff
let delay = 3000;
let result;
do {
  await new Promise((r) => setTimeout(r, delay));
  result = await fetch(`${BASE}/v1/pii/${jobId}`, {
    headers: { "X-API-Key": API_KEY },
  }).then((r) => r.json());
  delay = Math.min(delay * 1.5, 15000);
} while (!["completed", "failed"].includes(result.status));

if (result.status === "completed") {
  console.log(`Redacted file: ${result.redacted_file_url}`);
  console.log(`Total redactions: ${result.report.total_redactions}`);
}

cURL

# Redact a PDF
curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@document.pdf"

# Redact a scanned image
curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@id_card.png"

# Redact with language hint
curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@documento.pdf" \
  -F "language=es"

# Check status
curl https://api.deepread.tech/v1/pii/JOB_ID \
  -H "X-API-Key: $DEEPREAD_API_KEY"

Workflows: Combine with Other DeepRead Skills

Extract Then Redact

Use deepread-ocr to extract data, then redact the original before archiving:

# Step 1: Extract structured data (keeps the data you need)
curl -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"},"amount":{"type":"number"}}}'

# Step 2: Redact PII from original (clean copy for filing)
curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@claim.pdf"

Redact Before LLM Processing

Strip PII before sending document content to any AI model:

# 1. Redact the document
resp = requests.post(f"{BASE}/v1/pii/redact",
    headers={"X-API-Key": API_KEY},
    files={"file": open("report.pdf", "rb")})
job_id = resp.json()["id"]

# 2. Wait for completion, download redacted version
# 3. Now safe to send to any LLM for analysis

Fill Form Then Redact Copy

Use deepread-form-fill to complete a form, then redact a copy for records:

# Step 1: Fill the form
curl -X POST https://api.deepread.tech/v1/form-fill \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@w4_form.pdf" \
  -F 'form_fields={"full_name":"Jane Smith","ssn":"456-78-9012"}'

# Step 2: Redact the filled form for internal records
curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@w4_filled.pdf"

Best Practices

1. Use Webhooks for Production

curl -X POST https://api.deepread.tech/v1/pii/redact \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@document.pdf" \
  -F "webhook_url=https://your-app.com/webhooks/pii"

Only use polling if you cannot expose a webhook endpoint.

2. Review the Detection Report

The report tells you exactly what was found and where:

report = result["report"]

# Check if anything was below confidence threshold
if report["below_threshold_count"] > 0:
    print(f"Warning: {report['below_threshold_count']} detections below threshold")
    print("Consider manual review of the original document")

# See breakdown by type
for pii_type, summary in report["pii_detected"].items():
    print(f"{pii_type}: {summary['count']} on pages {summary['pages']}")

3. Set Language for Non-English Documents

Always specify the language for better detection accuracy:

-F "language=zh"   # Chinese
-F "language=es"   # Spanish
-F "language=hi"   # Hindi
-F "language=ar"   # Arabic

4. Polling Strategy

Poll every 3-5 seconds with backoff:

delay = 3
while True:
    time.sleep(delay)
    result = check_status(job_id)
    if result["status"] in ("completed", "failed"):
        break
    delay = min(delay * 1.5, 15)  # cap at 15s

Rate Limits & Pricing

Free Tier (No Credit Card)

2,000 pages/month
10 requests/minute (redact endpoint)
60 requests/minute (status endpoint)
Full feature access

Paid Plans

PRO: 50,000 pages/month, 100 req/min @ $99/mo
SCALE: Custom volume pricing

Upgrade: https://www.deepread.tech/dashboard/billing?utm_source=clawhub

Troubleshooting

Error: `UNSUPPORTED_FORMAT`

Solution: Only PDF, PNG, JPEG, and TXT are supported. Convert other formats first.

Error: `EMPTY_DOCUMENT`

Solution: File has no content. Check the file is not corrupted or zero-bytes.

Error: `FILE_TOO_LARGE`

Solution: Compress the file or split into smaller documents. Max 50MB.

No PII detected in report

Possible causes:

Document genuinely contains no PII
PII is in a language not specified (set language parameter)
Image quality too low for detection (try higher resolution scan)

Redaction missed some PII