Automatically extract, validate, and prepare data from your claims for easy processing.
Extract relevant information from files and images related to claims, automatically. Discover new operational insights, detect fraud, and avoid costly compliance fines.
Extract text and numbers from claims and supporting documents, whether they're PDFs, scanned images, Word documents, or even emails.
Impira’s technology learns the difference between your various claims & document formats. No need to work with brittle templates or an engineer.
Tell Impira when predictions are correct, and the accuracy will continually improve—without a data scientist.
Automatically ingest documents and files from emails, web portals, scanners, apps, messages, and more.
Integrate with your existing tools and continue your work, uninterrupted.
Search across all your records, for names, dates, addresses, and more.
Drag and drop your documents to upload. Work with any type of file, from PDFs to scanned images — our OCR technology will extract the information you need.
Using one document, highlight the information you want to extract. Impira will automatically find matches in your other documents, even if they’re different file types.
Impira will predict the data you want from your other documents. Review and confirm auto-generated matches to train the model and improve its accuracy and confidence.
Export your final data into a CSV file or access your data through a REST API.
Drag and drop your documents to upload. Work with any type of file, from PDFs to scanned images — our OCR technology will extract the information you need.
Using one document, highlight the information you want to extract. Impira will automatically find matches in your other documents, even if they’re different file types.
Impira will predict the data you want from your other documents. Review and confirm auto-generated matches to train the model and improve its accuracy and confidence.
Impira is onboarding new users every day. In order to get early access for free, sign up now.
