๐ŸŽฏ Most Popular

Document Queries (Batch)

Create reusable query collections for batch document processing. Define your questions once, then extract structured data from multiple documents with coordinates. Perfect for high-volume document workflows.

const formData = new FormData();
formData.append('document', file);
formData.append('processor_id', '123e4567-e89b-12d3-a456-426614174000');

const batchQueries = await fetch('/api/ask/batch', {
  method: 'POST',
  headers: { 'X-API-Key': 'your-api-key' },
  body: formData
});

const job = await batchQueries.json();
// { id: "987fcdeb-51a2-43d1-b456-426614174000", status: "queued" }

// Poll for completion
const statusResponse = await fetch(`/api/jobs/${job.id}`, {
  headers: { 'X-API-Key': 'your-api-key' }
});

const result = await statusResponse.json();
// Get extracted field data with coordinates
const invoiceTotal = result.data.find(field => field.field_name === 'invoice_total');
console.log('Value:', invoiceTotal.value); // "$1,234.56"
console.log('AI Answer:', invoiceTotal.ai_answer); // "The total amount is $1,234.56"
console.log('Coordinates:', invoiceTotal.geometry[0].bbox); // [100, 200, 300, 250]
Predefined batch of queries with coordinates
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Query Collections

Create reusable sets of questions for consistent extraction across documents

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Batch Processing

Process multiple documents with the same query set efficiently

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Structured Output

Get consistent JSON responses with coordinates for every field

Document Queries API Demo

Interactive demo coming soon...

Perfect For Your Workflow

Streamline document processing across industries

See how Document Queries fits into real-world applications

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Invoice Processing at Scale

Process hundreds of invoices daily with consistent field extraction

Example questions:

Automated AP workflows

Multi-vendor invoice processing

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Contract Management

Extract key terms and dates from large contract portfolios

Example questions:

Contract renewal tracking

Risk assessment automation

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Form Processing

Digitize paper forms and applications at scale

Example questions:

Customer onboarding

Survey data collection

Document Query vs Traditional Methods

Why natural language questions beat rigid templates

Replace complex OCR setup with simple questions that work on any document format

Unique: Natural language questions ("What's the total?") + coordinate proof for any document type

NinjadocAITemplate OCRGeneric LLM/AI API
โ“Natural Language Questions
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๐Ÿ“Answer + Coordinate Proof
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โšก5-Minute Integration
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๐Ÿ’ฒTransparent Pricing
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๐Ÿ”งTypeScript SDK + React Components
๐Ÿง Context Understanding
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๐ŸŽฏZero Configuration Required
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๐Ÿ“Handles Document Layout Variations
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๐Ÿ”ŒDeveloper-Friendly REST API
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Trusted by Teams Worldwide

Real results from real implementations

See how Document Queries is transforming document processing workflows

"Batch processing with query collections has streamlined our document workflows. We process hundreds of invoices daily with consistent results."

Robert Kim

Operations Manager

"Setting up query collections once and reusing them across documents saves us so much time. The structured output is perfect for our systems."

Lisa Wong

Data Analyst

Frequently Asked Questions

Everything you need to know

Get answers to common questions about Document Queries

How do query collections work?

Query collections allow you to define a set of questions once, then apply them to multiple documents. Each document gets processed with the same queries for consistent, structured output.

Can I modify query collections after creation?

Yes, you can update your query collections through our dashboard or API. Changes will apply to future document processing, but won't affect completed jobs.

What's the best use case for batch processing?

Batch processing is ideal for high-volume document processing where you need consistent extraction from similar document types, like invoices, contracts, or forms.