NanoNets is a Deep Learning web platform that makes it easier than ever before to use Deep Learning in practical applications. It combines the convenience of a web-based platform with Deep Learning models to create image recognition and object classification applications for your business. You can easily build and integrate deep learning models using NanoNets’ API. You can also work with our pre-trained models which have been trained on huge datasets and return accurate results. NanoNets has leveraged recent advances in Deep Learning to build rich representations of data which are transferable across tasks. It’s as simple as uploading your input, generating the output and getting a functioning and highly accurate Deep Learning model for your AI needs. NanoNets is revolutionary because it allows you to train models without large datasets. With just 100 images you can train a model on our platform to detect features and classify images with a high degree of accuracy. NanoNets benefits you in four important ways: ● It reduces the amount of data needed to build a Deep Learning Model ● NanoNets handles the infrastructure for hosting and training the model, and for the run time ● It reduces the cost of running deep learning models by sharing infrastructure across models ● It is possible for anyone to build a deep learning model
Algodocs is an intelligent document processing tool that harnesses AI technology to automate data extraction from business documents. Trusted by customers globally, Algodocs streamlines processes by offering fast, secure, and accurate extraction of document data.
The platform features AI-based intelligent extraction, rule-based extraction, and the enhancement of extracted data. Users can easily customize data extraction rules, handle business exceptions, and receive instant notifications for missing or incorrect data.
Algodocs also allows for automated exporting of extracted data to various applications and formats. With advanced features like handwriting recognition and automatic form key-value pairs and table extraction, Algodocs ensures high accuracy and efficiency in data processing.
Whether it's PDF invoices, bank statements, HR forms, receipts, or sales orders, Algodocs can extract data from virtually any document type without the need for templates or labeling training.
Use cases & applications
• ✔️ Automate the extraction of invoice data from PDF documents with Algodocs, saving time and reducing errors in financial record-keeping processes. • ✔️ Efficiently extract key information from HR forms using Algodocs' intelligent extraction capabilities, ensuring accurate and streamlined handling of sensitive employee data. • ✔️ Enhance the document processing workflow by extracting and exporting data from bank statements to various applications and formats seamlessly with Algodocs.
Based on our record, Nanonets seems to be more popular. It has been mentiond 6 times since March 2021. 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.
Want to automate repetitive manual tasks? Check our Nanonets workflow-based document processing software. Source: almost 3 years ago
Nanonets is a no-code, workflow-based, and AI-enhanced intelligent document processing platform. It automates all document processes and is built on a robust, intelligent, self-learning OCR API that allows users to extract required data from documents in minutes. Source: almost 3 years ago
Check out our website here https://nanonets.com/ for more. We also have some free tools where you can experience our product for free (like https://nanonets.com/online-ocr). Source: about 3 years ago
Here is another company, which I just came across by accident, which do the same: https://nanonets.com/. Source: about 3 years ago
We will be using Python3.6+, Django web framework, Nanonets for character extraction from an image, Cloudinary for image storage and Google Search API for performing the searches. - Source: dev.to / over 3 years ago
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