Kudra

Automatically extracts key financial data from invoice documents using OCR and LLM processing, converting unstructured invoice images or PDFs into structured JSON format with line items, amounts, dates, and vendor information.

Identifies and extracts specific clauses, obligations, and key terms from legal contracts, organizing them into structured data that highlights important sections like payment terms, liability limits, and renewal dates.

Extracts structured candidate information from resumes and application forms, including contact details, work experience, education, skills, and qualifications, converting unstructured documents into standardized JSON records.

Automatically detects form fields and extracts filled-in values from structured forms, including checkboxes, text fields, and dropdown selections, converting paper or digital forms into machine-readable JSON.

Processes multiple documents in bulk, extracting and structuring data from hundreds or thousands of files simultaneously, with results delivered in standardized JSON format for batch integration.

Converts extracted document data into clean, standardized JSON format that can be directly integrated with downstream systems, databases, and workflows without additional transformation.

Processes diverse document types (invoices, contracts, resumes, forms) with a single unified interface, automatically detecting document type and applying appropriate extraction logic without manual configuration.

Performs optical character recognition on document images to extract text content, handling scanned documents, photographs, and low-quality images to enable data extraction from non-digital sources.

Provides API endpoints for programmatically submitting documents for extraction and retrieving structured results, enabling integration with custom applications and workflows.

Offers free tier access allowing teams to test document extraction capabilities on a limited number of documents before committing to paid plans, reducing evaluation friction.