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“We are using Docsumo’s APIs for automating data capture from bank statements and identity cards while on-boarding customers. It has reduced the time our operations team spends on data entry by manifolds while providing a much better customer experience.”
Since the very beginning everything was fine, they always say “Ask anything even if you need support from our developers. The support for initial user was exceptional, even for small users like me.
Operations Manager, Onerz
“Bringing down the invoice processing time from a few hours to less than 5 minutes with 99%accuracy has been a real-game changer for us. With Docsumo, we have been able to automate invoice processing resulting in lower turnaround time and better customer experience.”
Founder & Managing Partner, ValtaTech
Extract data from ACORD forms and easily monitor insurance coverage with pre-built analytics.
Extract and process data from Aadhaar cards images, even when captured from mobile phones.
Scanning substandard quality driving license images is not a problem anymoredocuments with near 100% accuracy
Onboard customers in real time by capturing data from identity documents with near 100% accuracy
In today’s dynamic business world, filing and archiving official documents in the digital form makes it handy, and works wonders in the future or in unforeseen circumstances.
Optical Character Recognition(OCR) is a technology widely used to convert handwritten, typed, scanned text, or text inside images to machine-relatable text. Because of its ability, the technology is used for form processing amongst other document types. Based on the form use-case, different OCR solutions are used - for structured forms, template-based OCR is the answer, whereas for semi-structured and unstructured forms, a more sophisticated data extraction solution is required.
Lenders need to extract data from bank checks amongst other documents for account verification, and several technologies are used for this purpose. The data extraction from checks starts with scanning image/pdf files. After the check is scanned, OCR comes into picture that works to extract all the key-value pair and line items from the check based on the trained model. The algorithm of the check identification and OCR method does the rest of the job.
Invoice processing is done 2 ways: manual and automated. The manual invoice processing requires inputting information, confirming accuracy, and archiving documentation. On the other hand, Optical Character Recognition (OCR), a text-extracting technique is used to automate invoice processing that turns digitized documents into files that can be edited. In automated invoice processing, invoices are unit routed through centralized points of entry in an automatic system, therefore whether invoices arrive via email or other sources, the system processes them. This frees up time for team members to focus on more specialized jobs.
We’d love to show you how you can increase your productivity, process your documents faster and save operations cost!