Receipt OCR is a powerful technology that leverages artificial intelligence and machine learning to extract key data from receipts and other financial documents. As businesses increasingly move toward digital record keeping and automation, receipt OCR has become a vital tool for streamlining accounting, expense management and bookkeeping processes.Schedule a Demo
Streamline your receipt processing and expense/spend management with sophisticated automed workflows. Let your teams focus on maximizing revenue and minimizing costs.
Upload PDFs or images via email, API, desktop, Drive, Dropbox, RPA or cloud storage.
Intelligently capture information you need. Our interface lets you review this for highest veracity.
Connect with your existing system and apps for easy and efficient transition to our platform.
Take a moment to upload your own receipts and test Nanonets OCR capabilities. Get a firsthand look at how it works on your own documents.
No need to spend time training a receipt OCR model from scratch - our solution already recognizes a wide variety of receipt fields.
Say goodbye to errors and hello to real-time document processing. Nanonets takes care of this and lets you focus on what matters most - your business.
Capture or import data from any source or in any format including, images, PDFs, scans, paper documents, emails, cloud storage, APIs and more.
Our OCR APIs have been rigorously tested and pre-trained on millions of documents, ensuring high accuracy and reliability from day one.
Set up completely automated workflows to handle file imports, data formatting, data validation, approvals, exports and integrations.
Reduce time spent on inefficient manual tasks and avoid data entry or validation errors that could burn a hold in your pocket.
Integrate your existing business tools seamlessly with Nanonets to automate data collection, exports storage, bookkeeping, and much more.
Turn your organisation 10x more productive by allowing teams to focus entirely on core activities while Nanonets handles everything else.
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