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Parserdata is an AI-powered financial data extraction and automation platform designed to eliminate tedious manual data entry by intelligently extracting key structured information from unstructured financial documents, including invoices, receipts, transaction reports, bank statements, and balance sheets, without requiring templates or manual mapping. It uses machine learning and advanced scanning technology to recognize and pull out fields like vendor details, amounts, dates, and totals, delivering clean, structured output ready for analysis or integration into accounting systems, which dramatically reduces errors and saves time previously spent on copying, pasting, and reformatting data. It prioritizes data security and compliance through encryption and is built to scale with growing volumes of documents, so teams can streamline workflows across accounts payable and reporting processes.

PrecisionOCR is a ready-to-use, secure, HIPAA-compliant, cloud-based platform for extracting medical meaning from unstructured documents using Optical Character Recognition (OCR). PrecisionOCR uses custom Optical Character Recognition and AI algorithms to convert PDFs/JPEGs/PNGs into structured, searchable documents. Organizations can work with our team to build OCR report extractors which look for specific types of information to extract or highlight to reduce the noise that comes from extracting all of the data within a document. Natural language processing (NLP) and machine learning (ML) power the semi-automated and automated transformation of source material such as pdfs or images into structured data records that integrate seamlessly with EMR data using HL7s FHIR standards. Data can be automatically stored along side patient records. Our OCR document classification is also available along with multiple ways to integrate including API and CLI support.