Kudra vs Abridge

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.

Captures and transcribes patient-clinician conversations in real-time during clinical encounters. Converts spoken dialogue into text format while preserving medical terminology and context.

Automatically generates structured clinical notes from conversation transcripts using medical AI. Produces documentation that follows clinical standards and includes relevant sections like assessment, plan, and history of present illness.

Directly integrates with Epic electronic health record system to automatically populate generated clinical notes into patient records. Eliminates manual data entry and ensures documentation flows seamlessly into existing workflows.

Ensures all patient conversations, transcripts, and generated documentation are processed and stored in compliance with HIPAA regulations. Implements security protocols for protected health information throughout the documentation workflow.

Processes patient-clinician conversations in multiple languages and generates documentation in the appropriate language. Enables healthcare delivery across diverse patient populations with different primary languages.

Accurately identifies and standardizes medical terminology, abbreviations, and clinical concepts from conversations. Ensures documentation uses correct medical language and coding-ready terminology.