Docsumo is an intelligent document processing platform for financial services firms. Docsumo helps businesses and enterprises extract data from documents, analyze that data and detect document fraud.
Docsumo’s technology reduces back-office costs by up to 70% and increases productivity by 50%. For every million documents processed by a bank at about $1 per document, DocSumo can directly save $700k. What differentiates Docsumo is that their technology can read non-standardised documents such as bank statements, invoices, pay stubs and contracts with over 99% accuracy and more than 95% straight-through processing.
Docsumo features include:-
✅Data Capture from forms, semi-structured and unstructured financial documents ✅Pre-Trained API stack for loan application, insurance compliance, invoices, supply chain management, and Commercial Real Estate applications ✅Review & edit tool that allows you to click on any text in a document to capture data without manual entry ✅Out of the box API endpoint (accessible via Settings page) & option to download CSV ✅Multiple learning mechanism to ensure maximum accuracy ✅Simple pay as you go pricing ✅Ability to customize fields from the frontend ✅Define templates for recurring documents ✅Self-train neural network on your dataset
Choose Docsumo, if you want to:- - Automate the document data extraction end-to-end - Efficiently scale your process and your business eliminating manual data entry - Reduce risk by validating data
Based on our record, Amazon Rekognition seems to be a lot more popular than Docsumo. While we know about 33 links to Amazon Rekognition, we've tracked only 2 mentions of Docsumo. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
AWS Rekognition is a great choice for many types of real-world projects or just for testing an idea on your images. The issue eventually comes with its cost, unfortunately, which we will see later in a specific example. Don’t get me wrong, Rekognition is a great service and I love to use it for its simplicity and reliable performance on quite a few projects. - Source: dev.to / about 1 month ago
I don’t really want to spend so much time manually adjusting labels. For most machine learning, the next step would be to fine tune your model. You can essentially fine tune Amazon Rekognition by using Custom Labels. You can do this to make it better at detecting specific objects (like bears) or train it to detect new objects like your product or logo. It really depends on your application needs. - Source: dev.to / 9 months ago
For instance, are you a company with lots of security cameras? Hire me to write a program that pipes your data into AWS rekognition and then shows you a dashboard of what happened on your cams today. Got a ton of products with no meta-description? Hire me to write a program that pipes your data into OpenAI, and then saves the generated description to your custom CMS. Source: 10 months ago
Amazon Rekognition: Used to index, detect faces in the picture, and compare faces when users try voting, it was the heart of the facial voting feature. - Source: dev.to / almost 1 year ago
Sure. But if you think generating thumbnails and detecting intros/credits takes a long time, wait until your computer is running machine learning/computer vision over your entire library. They also have to build and train that model which is no trivial task. And I know what you're thinking, why don't they just use Amazon's Rekognition service that does celebrity identification? Well, it's $0.10 per minute of... Source: about 1 year ago
Aayush here from Docsumo.com, we are a Document AI platform that empowers tech & ops teams to scale operations effortlessly by capturing, validating & analyzing unstructured documents. We recently raised $3.5 Million from Marquee investors. Source: over 1 year ago
Check out our website https://docsumo.com/ and blog https://docsumo.com/blog for more details. Source: over 1 year ago
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