Author: Ben SmithBased in Tokyo, Ben Smith is the Chief Technology Officer and Head of Research at Tabscanner. He pioneers deep learning models specifically designed for receipt optical character recognition (OCR) and document classification, engineering the core AI architectures that enable high-accuracy data extraction.

Using OCR Receipt Technology Will Add Significant Value to All Your Accountancy and Bookkeeping Practices

Using OCR Receipt Technology Will Add Significant Value to All Your Accountancy and Bookkeeping Practices

Whether you’ve diligently kept abreast of recent OCR developments or are a total greenhorn when it comes to optical character recognition, it’s fair to say that the technology has the power to revolutionise expense management. Long resigned to forecasted innovation – even a technology that our children may find integral to managing their finances – performing an OCR scan […]

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Five Ways that Accountants Can Use an OCR Receipt Scanner and Similar Technology to Optimise Growth Strategies

Five Ways that Accountants Can Use an OCR Receipt Scanner and Similar Technology to Optimise Growth Strategies

If there’s one word that’s universally-applicable to businesses of all descriptions the world over its progression. Managing directors must, not only make astute decisions with the present circumstances of their business but, have one eye on the future. This ethos allows businesses to better service their clients, grow their client base and increase revenue. Accountancy […]

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Three Ways Your Business Will Benefit from OCR Receipt Technology

Three Ways Your Business Will Benefit from OCR Receipt Technology

Just a few short years ago, the thought of having a paperless business seemed little more than a pipe dream. Desks were littered with documents; waste paper baskets were filled to the brim with crumpled paper balls and lined pads were distributed like they were going out of fashion. These days all that has changed. The digital revolution has substantially reduced […]

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Customer Loyalty Rewards with Receipt OCR in E-Commerce: 3 Commanding Examples

Customer Loyalty Rewards with Receipt OCR in E-Commerce: 3 Commanding Examples

Loyalty Rewards with Receipt OCR – 3 Examples with the Tabscanner API As any business owner will tell you, acquiring new customers isn’t always as easy as we’d like to think. It’s not as simple as designing and optimising a website, making a handful of phone calls, attending trade events and then waiting for the […]

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Which Tool for Automated Receipt Clearing in Loyalty Programs

Which Tool for Automated Receipt Clearing in Loyalty Programs

Ben SmithBased in Tokyo, Ben Smith is the Chief Technology Officer and Head of Research at Tabscanner. He pioneers deep learning models specifically designed for receipt optical character recognition (OCR) and document classification, engineering the core AI architectures that enable high-accuracy data extraction. www.linkedin.com/in/tokyoben/

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Receipt OCR in Expense Management, Loyalty Rewards, and Market Research

Receipt OCR in Expense Management, Loyalty Rewards, and Market Research

Receipt OCR in Expense Management and more Receipt Optical Character Recognition (OCR) technology has revolutionized how businesses handle financial data and customer interactions. By automating the extraction of information from receipts, OCR is driving efficiency and unlocking valuable insights. This article explores three primary use cases of a receipt OCR API: expense management, loyalty rewards […]

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Tabscanner Data Refinement: Achieving Peak OCR Technology Accuracy through the additional training of models

Tabscanner Data Refinement: Achieving Peak OCR Technology Accuracy through the additional training of models

Tabscanner Data Refinement: Achieving Peak Accuracy for OCR Technology through the additional training of models In the complex landscape of receipt OCR technology, achieving high levels of accuracy is crucial for businesses that depend on detailed data extraction from various receipt formats. At Tabscanner, we understand that the needs of our clients can be intricate […]

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