deepread

OCR that never fails silently. Multi-pass document processing API with intelligent quality review flags. Extract text and structured data from PDFs with AI-powered confidence scoring. Free tier - 2,000 pages/month.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "deepread" with this command: npx skills add sundial-org/awesome-openclaw-skills/sundial-org-awesome-openclaw-skills-deepread

DeepRead - Production OCR API

OCR that never fails silently. Process PDFs and extract structured data with AI-powered confidence scoring that tells you exactly which fields need human review.

What This Skill Does

DeepRead is a production-grade document processing API that reduces human review from 100% to ~10% through intelligent quality assessment.

Core Features:

  • Text Extraction: Convert PDFs to clean markdown
  • Structured Data: Extract JSON fields with confidence scores
  • Quality Flags: AI determines which fields need human verification (hil_flag)
  • Multi-Pass Processing: Multiple validation passes for maximum accuracy
  • Multi-Model Consensus: Cross-validation between models for reliability
  • Free Tier: 2,000 pages/month (no credit card required)

Setup

1. Get Your API Key

Sign up and create an API key:

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

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

Save your API key:

export DEEPREAD_API_KEY="sk_live_your_key_here"

2. Clawdbot Configuration (Optional)

Add to your clawdbot.config.json5:

{
  skills: {
    entries: {
      "deepread": {
        enabled: true,
        apiKey: "sk_live_your_key_here"
      }
    }
  }
}

3. Process Your First Document

Option A: With Webhook (Recommended)

# Upload PDF with webhook notification
curl -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@document.pdf" \
  -F "webhook_url=https://your-app.com/webhooks/deepread"

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

# Your webhook receives results when processing completes (2-5 minutes)

Option B: Poll for Results

# Upload PDF without webhook
curl -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@document.pdf"

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

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

Usage Examples

Basic OCR (Text Only)

Extract text as clean markdown:

# With webhook (recommended)
curl -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@invoice.pdf" \
  -F "webhook_url=https://your-app.com/webhook"

# OR poll for completion
curl -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@invoice.pdf"

# Then poll
curl https://api.deepread.tech/v1/jobs/JOB_ID \
  -H "X-API-Key: $DEEPREAD_API_KEY"

Response when completed:

{
  "id": "550e8400-...",
  "status": "completed",
  "result": {
    "text": "# INVOICE\n\n**Vendor:** Acme Corp\n**Total:** $1,250.00..."
  }
}

Structured Data Extraction

Extract specific fields with confidence scoring:

curl -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@invoice.pdf" \
  -F 'schema={
    "type": "object",
    "properties": {
      "vendor": {
        "type": "string",
        "description": "Vendor company name"
      },
      "total": {
        "type": "number",
        "description": "Total invoice amount"
      },
      "invoice_date": {
        "type": "string",
        "description": "Invoice date in MM/DD/YYYY format"
      }
    }
  }'

Response includes confidence flags:

{
  "status": "completed",
  "result": {
    "text": "# INVOICE\n\n**Vendor:** Acme Corp...",
    "data": {
      "vendor": {
        "value": "Acme Corp",
        "hil_flag": false,
        "found_on_page": 1
      },
      "total": {
        "value": 1250.00,
        "hil_flag": false,
        "found_on_page": 1
      },
      "invoice_date": {
        "value": "2024-10-??",
        "hil_flag": true,
        "reason": "Date partially obscured",
        "found_on_page": 1
      }
    },
    "metadata": {
      "fields_requiring_review": 1,
      "total_fields": 3,
      "review_percentage": 33.3
    }
  }
}

Complex Schemas (Nested Data)

Extract arrays and nested objects:

curl -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@invoice.pdf" \
  -F 'schema={
    "type": "object",
    "properties": {
      "vendor": {"type": "string"},
      "total": {"type": "number"},
      "line_items": {
        "type": "array",
        "items": {
          "type": "object",
          "properties": {
            "description": {"type": "string"},
            "quantity": {"type": "number"},
            "price": {"type": "number"}
          }
        }
      }
    }
  }'

Page-by-Page Breakdown

Get per-page OCR results with quality flags:

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

Response:

{
  "result": {
    "text": "Combined text from all pages...",
    "pages": [
      {
        "page_number": 1,
        "text": "# Contract Agreement\n\n...",
        "hil_flag": false
      },
      {
        "page_number": 2,
        "text": "Terms and C??diti??s...",
        "hil_flag": true,
        "reason": "Multiple unrecognized characters"
      }
    ],
    "metadata": {
      "pages_requiring_review": 1,
      "total_pages": 2
      }
  }
}

When to Use This Skill

✅ Use DeepRead For:

  • Invoice Processing: Extract vendor, totals, line items
  • Receipt OCR: Parse merchant, items, totals
  • Contract Analysis: Extract parties, dates, terms
  • Form Digitization: Convert paper forms to structured data
  • Document Workflows: Any process requiring OCR + data extraction
  • Quality-Critical Apps: When you need to know which extractions are uncertain

❌ Don't Use For:

  • Real-time Processing: Processing takes 2-5 minutes (async workflow)
  • Batch >2,000 pages/month: Upgrade to PRO or SCALE tier

How It Works

Multi-Pass Pipeline

PDF → Convert → Rotate Correction → OCR → Multi-Model Validation → Extract → Done

The pipeline automatically handles:

  • Document rotation and orientation correction
  • Multi-pass validation for accuracy
  • Cross-model consensus for reliability
  • Field-level confidence scoring

Quality Review (hil_flag)

AI compares extracted text to the original image and sets hil_flag:

  • hil_flag: false = Clear, confident extraction → Auto-process
  • hil_flag: true = Uncertain extraction → Human review required

AI flags extractions when:

  • Text is handwritten, blurry, or low quality
  • Multiple possible interpretations exist
  • Characters are partially visible or unclear
  • Field not found in document

This is multimodal AI determination, not rule-based.

Advanced Features

1. Blueprints (Optimized Schemas)

Create reusable, optimized schemas for specific document types:

# List your blueprints
curl https://api.deepread.tech/v1/blueprints \
  -H "X-API-Key: $DEEPREAD_API_KEY"

# Use blueprint instead of inline schema
curl -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@invoice.pdf" \
  -F "blueprint_id=660e8400-e29b-41d4-a716-446655440001"

Benefits:

  • 20-30% accuracy improvement over baseline schemas
  • Reusable across similar documents
  • Versioned with rollback support

How to create blueprints:

# Create a blueprint from training data
curl -X POST https://api.deepread.tech/v1/optimize \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "utility_invoice",
    "description": "Optimized for utility invoices",
    "document_type": "invoice",
    "initial_schema": {
      "type": "object",
      "properties": {
        "vendor": {"type": "string", "description": "Vendor name"},
        "total": {"type": "number", "description": "Total amount"}
      }
    },
    "training_documents": ["doc1.pdf", "doc2.pdf", "doc3.pdf"],
    "ground_truth_data": [
      {"vendor": "Acme Power", "total": 125.50},
      {"vendor": "City Electric", "total": 89.25}
    ],
    "target_accuracy": 95.0,
    "max_iterations": 5
  }'

# Returns: {"job_id": "...", "blueprint_id": "...", "status": "pending"}

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

# Use blueprint (once completed)
curl -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@invoice.pdf" \
  -F "blueprint_id=BLUEPRINT_ID"

2. Webhooks (Recommended for Production)

Get notified when processing completes instead of polling:

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

Your webhook receives this payload when processing completes:

{
  "job_id": "550e8400-...",
  "status": "completed",
  "created_at": "2025-01-27T10:00:00Z",
  "completed_at": "2025-01-27T10:02:30Z",
  "result": {
    "text": "...",
    "data": {...}
  },
  "preview_url": "https://preview.deepread.tech/abc1234"
}

Benefits:

  • No polling required
  • Instant notification when done
  • Lower latency
  • Better for production workflows

3. Public Preview URLs

Share OCR results without authentication:

# Request preview URL
curl -X POST https://api.deepread.tech/v1/process \
  -H "X-API-Key: $DEEPREAD_API_KEY" \
  -F "file=@document.pdf" \
  -F "include_images=true"

# Get preview URL in response
{
  "result": {
    "text": "...",
    "data": {...}
  },
  "preview_url": "https://preview.deepread.tech/Xy9aB12"
}

Public Preview Endpoint:

# No authentication required
curl https://api.deepread.tech/v1/preview/Xy9aB12

Rate Limits & Pricing

Free Tier (No Credit Card)

  • 2,000 pages/month
  • 10 requests/minute
  • Full feature access (OCR + structured extraction + blueprints)

Paid Plans

  • PRO: 50,000 pages/month, 100 requests/minute @ $99/mo
  • SCALE: Custom volume pricing (contact sales)

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

Rate Limit Headers

Every response includes quota information:

X-RateLimit-Limit: 2000
X-RateLimit-Remaining: 1847
X-RateLimit-Used: 153
X-RateLimit-Reset: 1730419200

Best Practices

1. Use Webhooks for Production

✅ Recommended: Webhook notifications

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

Only use polling if:

  • Testing/development
  • Cannot expose a webhook endpoint
  • Need synchronous response

2. Schema Design

✅ Good: Descriptive field descriptions

{
  "vendor": {
    "type": "string",
    "description": "Vendor company name. Usually in header or top-left of invoice."
  }
}

❌ Bad: No description

{
  "vendor": {"type": "string"}
}

3. Polling Strategy (If Needed)

Only if you can't use webhooks, poll every 5-10 seconds:

import time
import requests

def wait_for_result(job_id, api_key):
    while True:
        response = requests.get(
            f"https://api.deepread.tech/v1/jobs/{job_id}",
            headers={"X-API-Key": api_key}
        )
        result = response.json()

        if result["status"] == "completed":
            return result["result"]
        elif result["status"] == "failed":
            raise Exception(f"Job failed: {result.get('error')}")

        time.sleep(5)

4. Handling Quality Flags

Separate confident fields from uncertain ones:

def process_extraction(data):
    confident = {}
    needs_review = []

    for field, field_data in data.items():
        if field_data["hil_flag"]:
            needs_review.append({
                "field": field,
                "value": field_data["value"],
                "reason": field_data.get("reason")
            })
        else:
            confident[field] = field_data["value"]

    # Auto-process confident fields
    save_to_database(confident)

    # Send uncertain fields to review queue
    if needs_review:
        send_to_review_queue(needs_review)

Troubleshooting

Error: quota_exceeded

{"detail": "Monthly page quota exceeded"}

Solution: Upgrade to PRO or wait until next billing cycle.

Error: invalid_schema

{"detail": "Schema must be valid JSON Schema"}

Solution: Ensure schema is valid JSON and includes type and properties.

Error: file_too_large

{"detail": "File size exceeds 50MB limit"}

Solution: Compress PDF or split into smaller files.

Job Status: failed

{"status": "failed", "error": "PDF could not be processed"}

Common causes:

  • Corrupted PDF file
  • Password-protected PDF
  • Unsupported PDF version
  • Image quality too low for OCR

Example Schema Templates

Invoice Schema

{
  "type": "object",
  "properties": {
    "invoice_number": {
      "type": "string",
      "description": "Unique invoice ID"
    },
    "invoice_date": {
      "type": "string",
      "description": "Invoice date in MM/DD/YYYY format"
    },
    "vendor": {
      "type": "string",
      "description": "Vendor company name"
    },
    "total": {
      "type": "number",
      "description": "Total amount due including tax"
    },
    "line_items": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "description": {"type": "string"},
          "quantity": {"type": "number"},
          "price": {"type": "number"}
        }
      }
    }
  }
}

Receipt Schema

{
  "type": "object",
  "properties": {
    "merchant": {
      "type": "string",
      "description": "Store or merchant name"
    },
    "date": {
      "type": "string",
      "description": "Transaction date"
    },
    "total": {
      "type": "number",
      "description": "Total amount paid"
    },
    "items": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": {"type": "string"},
          "price": {"type": "number"}
        }
      }
    }
  }
}

Contract Schema

{
  "type": "object",
  "properties": {
    "parties": {
      "type": "array",
      "items": {"type": "string"},
      "description": "Names of all parties in the contract"
    },
    "effective_date": {
      "type": "string",
      "description": "Contract start date"
    },
    "term_length": {
      "type": "string",
      "description": "Duration of contract"
    },
    "termination_clause": {
      "type": "string",
      "description": "Conditions for termination"
    }
  }
}

Support & Resources

Important Notes

  • Processing Time: 2-5 minutes (async, not real-time)
  • Async Workflow: Use webhooks (recommended) or polling
  • Rate Limits: 10 req/min on free tier
  • File Size Limit: 50MB per file
  • Supported Formats: PDF, JPG, JPEG, PNG

Ready to start? Get your free API key at https://www.deepread.tech/dashboard/?utm_source=clawdhub

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Open in GitHubOpen in ClawHub

Related Skills

Related by shared tags or category signals.

General

ontology

No summary provided by upstream source.

Repository SourceNeeds Review
1.2K-sundial-org
General

exa-web-search-free

No summary provided by upstream source.

Repository SourceNeeds Review
1.2K-sundial-org
General

stock-market-pro

No summary provided by upstream source.

Repository SourceNeeds Review
900-sundial-org
General

finance-news

No summary provided by upstream source.

Repository SourceNeeds Review
465-sundial-org