Nanonets
DocParser
Docsumo
Rossum
Veryfi
DocuClipper
Nanonets OCR
Invoice Data Extraction
ArangoDB
Redis
MongoDB
neo4j
OrientDB
Apache Cassandra
Azure Cosmos DB
CouchBase
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
Nanonets ArangoDBNanonets is particularly recommended for businesses of all sizes that deal with large volumes of documents and require efficient data extraction and automation. Industries like finance, healthcare, logistics, and retail, which often handle invoices, forms, and contracts, can benefit significantly. It's also suitable for developers looking for an API solution to integrate OCR capabilities into their own applications.
ArangoDB might be a bit more popular than Nanonets. We know about 6 links to it since March 2021 and only 6 links to Nanonets. 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: about 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: about 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: over 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
If you like the document db idea there are a lot of choices, especially https://arangodb.com/ which I think gets little attention because people who use it see it as a secret weapon. Too bad about the license though. Also https://couchdb.apache.org/ and https://developer.marklogic.com/. - Source: Hacker News / 10 months ago
ArangoDB is a multi-model database that supports document, key-value, and graph data models with a unified query language. - Source: dev.to / 12 months ago
In modern databases, efficient data serialization and deserialization are paramount to achieving high performance. ArangoDB, a multi-model database, addresses this need with its innovative binary data format, VelocyPack. This article delves into the intricacies of VelocyPack, demonstrating its advantages, usage, and how it enhances the performance of ArangoDB with code examples in Java and Rust. - Source: dev.to / about 1 year ago
ArangoDB: A native multi-model database, it offers flexibility for documents, graphs, and key-values. This versatility makes it suitable for applications requiring a combination of these data models. - Source: dev.to / over 1 year ago
ArangoDB, a "multi-modal" database engine that stores arbitrary JSON documents like MongoDB, key/value data like Redis, and graph relationships like Neo4j — and lets you leverage all three kinds of data in a single query. Source: over 2 years ago
DocParser - Extract data from PDF files & automate your workflow with our reliable document parsing software. Convert PDF files to Excel, JSON or update apps with webhooks.
Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.
MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.
Rossum - Rossum is AI-powered, cloud-based invoice data capture service that speeds up invoice processing 6x, with up to 98% accuracy. It can be easily customized, integrated and scaled according to your company needs.
neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.
