OCR PDF to Structured JSON Bridge

OCR PDF to Structured JSON Bridge | Online Free Tool | Elysia Tools

Tool usage guide

Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Category: Document Tools
Input types: file, textarea, select
Output type: html
Sample coverage: 4
API ready: Yes

Overview

Extract text, key-value pairs, and table data from text-based PDF documents and map them directly into a target JSON Schema. The bridge analyzes layout geometry, font sizes, and delimiter patterns, coerces extracted strings into declared schema types, and validates the resulting JSON payload with Ajv.

When to use

When you need to extract structured data from PDF invoices, receipts, or purchase orders into a strict JSON Schema.
When converting semi-structured PDF reports containing tables and key-value pairs into schema-validated JSON for API ingestion.
When automating data entry from standard PDF forms into downstream databases while enforcing type coercion and schema rules.

How it works

1Upload a text-based PDF document and provide your target JSON Schema definition.
2Select the number coercion style (auto, dot decimal, or comma decimal) to ensure currency and numerical amounts parse accurately.
3The tool parses PDF layout geometry—detecting lines, headings, colon key-value pairs, and column-separated tables—and matches them to schema keys.
4Extracted values are coerced to declared schema types and validated with Ajv, returning an extraction mapping table and validated JSON output.

Use cases

Extracting invoice numbers, issue dates, and line items from vendor PDF invoices into ERP-ready JSON.
Transforming monthly financial statement PDFs into standardized JSON objects for automated ledger updates.
Parsing structured utility bills and service order PDFs into strictly typed records for backend database ingestion.

Examples

1. ERP Invoice Ingestion

Accounts Payable Automation Engineer

Background

Invoices arrive as text-based PDFs with variable layouts, including colon-separated headers, date formats, and line item tables.

Problem

Standardize invoice attributes and financial totals into typed fields conforming to an internal JSON Schema.

How to use

Upload the invoice PDF, paste the ERP JSON Schema requiring invoice_number, invoice_date, and numeric total, and set number style to 'auto'.

{
  "type": "object",
  "properties": {
    "invoice_number": { "type": "string" },
    "invoice_date": { "type": "string", "format": "date" },
    "customer": { "type": "string" },
    "currency": { "type": "string", "enum": ["USD", "EUR"] },
    "total": { "type": "number" }
  },
  "required": ["invoice_number", "total"]
}

Outcome

Produces a validated JSON object with normalized ISO dates and numeric values stripped of currency symbols, passing Ajv checks with zero errors.

2. Validating Schema Enum and Type Constraints

Integration Developer

Background

A backend service requires strict currency enums ('EUR', 'GBP') and integer amounts for payment clearing.

Problem

Detect incompatible PDF currency symbols and non-integer amounts before sending data to downstream APIs.

FAQ

Does this tool work on scanned image-only PDFs?

No, the PDF must contain a selectable text layer for layout geometry extraction.

How does the tool match PDF fields to schema properties?

It matches key-value labels and table headers against normalized property names defined in your JSON Schema.

What number formatting options are supported?

You can choose Auto, Dot decimal (e.g., 1,234.50), or Comma decimal (e.g., 1.234,50) for number coercion.

What happens if an extracted value violates schema rules?

Ajv flags the validation error at the exact JSON path while still displaying the raw extracted mapping and generated JSON.

What schema types and formats can be coerced?

It coerces string values to numbers, integers, booleans, and ISO date strings matching declared schema types and formats.

{
  "type": "object",
  "properties": {
    "invoice_number": { "type": "string" },
    "currency": { "type": "string", "enum": ["EUR", "GBP"] },
    "total": { "type": "integer" }
  },
  "required": ["invoice_number"]
}

Run this tool

Examples that match this tool

Continue with connected tools and hubs

Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Overview

When to use

How it works

Use cases

Examples

1. ERP Invoice Ingestion

2. Validating Schema Enum and Type Constraints

FAQ

PDF Samples

Chat Transcript JSON Samples

Rich Media JSON Samples

Terraform Plan JSON Samples

Chat Transcript to PDF

Fitness Workout PDF Generator

Rich Text JSON to PDF

PDF to JSON Structure Explorer