NinjaDoc Ai

NinjaDoc Ai

NinjaDoc AI is a document Q&A platform that enables developers to extract structured data from documents using natural language questions while providing exact coordinate proof, without requiring training or complex setup.
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NinjaDoc Ai

Product Information

Updated:Aug 28, 2025

What is NinjaDoc Ai

NinjaDoc AI is an innovative document processing platform specifically designed for developers who need to extract structured data from various types of documents. It combines the power of natural language processing with technical precision, offering a unique approach where users can build extraction schemas by simply asking questions about documents. The platform provides a developer-friendly REST API solution that eliminates the complexity typically associated with document data extraction, while offering 1,250 free credits to get started.

Key Features of NinjaDoc Ai

NinjaDoc AI is a document Q&A platform that enables developers to extract structured data from documents using natural language questions. It combines Q&A-based schema building with a REST API for data extraction, providing exact coordinate proof for extracted information. The platform offers zero-configuration setup, handles multiple document types, and provides precise coordinate-based extraction with 95%+ accuracy, eliminating the need for complex OCR integration or template maintenance.
Q&A Schema Builder: Build extraction schemas by simply asking natural language questions like 'What's the total?' or specifying technical field names, creating reusable processors for any document type
Coordinate-Based Extraction: Provides exact bounding box coordinates for every extracted field, perfect for verification and highlighting in downstream visual systems
Developer-Friendly REST API: Clean API integration that allows sending documents with processor IDs to receive structured data with coordinates, designed for quick implementation
Multi-Document Processing: Handles diverse document types within categories using a single schema, eliminating the need for individual templates per document

Use Cases of NinjaDoc Ai

Invoice Processing: Extract total amounts, line items, and other financial data from various invoice formats with coordinate proof
Contract Analysis: Extract key terms, dates, and clauses from legal documents with precise location information
Healthcare Documentation: Process medical records and forms to extract patient information, diagnoses, and treatment details with accuracy
Automated Data Entry: Replace manual document review and data entry workflows with automated extraction across multiple document types

Pros

No training or complex setup required
Pay-per-use pricing model starting at $10
High accuracy (95%+) with coordinate proof
Developer-friendly implementation

Cons

Credit-based system may increase costs for high-volume processing
Limited to document extraction use cases

How to Use NinjaDoc Ai

Step 1: Sign Up: Create an account on Ninjadoc AI platform to receive 1,250 free welcome credits
Step 2: Build Extraction Schema: Ask natural language questions like 'What's the total?' or specify technical field names to define what data you want to extract from documents
Step 3: Get Processor ID: Once you've created your extraction schema, you'll receive a processor_id that you can use for future extractions
Step 4: Integrate REST API: Use the REST API by sending your documents along with the processor_id to extract data. The API will return structured JSON with exact coordinates
Step 5: Process Documents: Upload documents through the API to get structured data extraction with coordinate proof for each field
Step 6: Monitor Results: Use the dashboard to monitor API usage, processing times, extraction confidence scores, and manage your schemas and documents
Step 7: Scale Usage: Purchase more credits as needed - 4,500 credits for $10, 10,000 credits for $25, or 50,000 credits for $100. Each page costs 25 credits plus 5 credits per extracted field

NinjaDoc Ai FAQs

NinjaDoc AI is the first Document Q&A platform that allows users to extract structured data from documents by asking natural language questions. It provides exact coordinate proof for extracted information and offers a developer-friendly REST API for integration.

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