DeepRead - Production OCR API

DeepRead is an AI-native OCR platform that turns documents into high-accuracy data in minutes. Using multi-model consensus, DeepRead achieves 97%+ accuracy and flags only uncertain fields for Human-in-the-Loop (HIL) review—reducing manual work from 100% to 5-10%. Zero prompt engineering required.

What This Skill Does

DeepRead is a production-grade document processing API that gives you high-accuracy structured data output in minutes with human review flagging so manual review is limited to the flagged exceptions

Core Features:

Text Extraction: Convert PDFs and images to clean markdown
Structured Data: Extract JSON fields with confidence scores
HIL Interface: Built-in Human-in-the-Loop review — uncertain fields are flagged (
```
hil_flag
```
) so only exceptions need manual review
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

# 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
        // API key is read from DEEPREAD_API_KEY environment variable
        // Do NOT hardcode your API 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

Human-in-the-Loop (HIL) Interface

DeepRead includes a built-in Human-in-the-Loop (HIL) review system. The AI compares extracted text to the original image and sets

hil_flag

on each field:

hil_flag: false
= Clear, confident extraction → Auto-process
hil_flag: true
= Uncertain extraction → Routed to human review

How HIL works:

Fields extracted with high confidence are auto-approved
Uncertain fields are flagged with
```
hil_flag: true
```
and a
```
reason
```
Only flagged fields need human review (typically 5-10% of total fields)
Review flagged fields in DeepRead Preview (
```
preview.deepread.tech
```
) — a dedicated HIL review interface where reviewers can see the original document side-by-side with extracted data, correct flagged fields, and approve results
Or integrate with your own review queue using the
```
hil_flag
```
data in the API response

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. Preview (HIL Review Interface)

DeepRead Preview (

preview.deepread.tech

) is the built-in Human-in-the-Loop review interface. Reviewers can view the original document alongside extracted data, correct flagged fields, and approve results. Preview URLs can also be shared 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[&quot;status&quot;] == &quot;completed&quot;:
        return result[&quot;result&quot;]
    elif result[&quot;status&quot;] == &quot;failed&quot;:
        raise Exception(f&quot;Job failed: {result.get(&#x27;error&#x27;)}&quot;)

    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[&quot;hil_flag&quot;]:
        needs_review.append({
            &quot;field&quot;: field,
            &quot;value&quot;: field_data[&quot;value&quot;],
            &quot;reason&quot;: field_data.get(&quot;reason&quot;)
        })
    else:
        confident[field] = field_data[&quot;value&quot;]

# 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

GitHub: https://github.com/deepread-tech
Issues: https://github.com/deepread-tech/deep-read-service/issues
Email: hello@deepread.tech

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

BYOK — Bring Your Own Key

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

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

Related DeepRead Skills

deepread-ocr — Extract text and structured JSON from documents (this skill) —
```
clawhub install uday390/deepread-ocr
```
deepread-form-fill — Fill any PDF form with AI vision —
```
clawhub install uday390/deepread-form-fill
```
deepread-pii — Redact 14 types of PII from documents —
```
clawhub install uday390/deepread-pii
```
deepread-agent-setup — Authenticate via OAuth device flow —
```
clawhub install uday390/deepread-agent-setup
```
deepread-byok — Bring Your Own Key setup —
```
clawhub install uday390/deepread-byok
```

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

DeepRead OCR

AI Skill Market Insights

Be Part of the 0+ Developer Community

DeepRead - Production OCR API

What This Skill Does

Setup

1. Get Your API Key

Or use this direct link

2. Clawdbot Configuration (Optional)

3. Process Your First Document

Returns immediately

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

Returns immediately

Poll until completed

Usage Examples

Basic OCR (Text Only)

OR poll for completion

Then poll

Structured Data Extraction

Complex Schemas (Nested Data)

Page-by-Page Breakdown

When to Use This Skill

✅ Use DeepRead For:

❌ Don't Use For:

How It Works

Multi-Pass Pipeline

Human-in-the-Loop (HIL) Interface

Advanced Features

1. Blueprints (Optimized Schemas)

Use blueprint instead of inline schema

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

Check optimization status

Use blueprint (once completed)

2. Webhooks (Recommended for Production)

3. Preview (HIL Review Interface)

Get preview URL in response

Rate Limits & Pricing

Free Tier (No Credit Card)

Paid Plans

Rate Limit Headers

Best Practices

1. Use Webhooks for Production

2. Schema Design

3. Polling Strategy (If Needed)

4. Handling Quality Flags

Troubleshooting

Error: quota_exceeded

Error: invalid_schema

Error: file_too_large

Job Status: failed

Example Schema Templates

Invoice Schema

Receipt Schema

Contract Schema

Support & Resources

Important Notes

BYOK — Bring Your Own Key

Related DeepRead Skills

Quick Start

Manual Installation

TEAR & SHARE

Tags

Channels

Learn

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Company

Error:
`quota_exceeded`

Error:
`invalid_schema`

Error:
`file_too_large`

Job Status:
`failed`