Micronaut Framework
vert.x
helidon
Javalin
GatsbyJS
Ktor
Serverless
Spring
DocParser
Nanonets
Parseur.com
Rossum
Docsumo
FlexiCapture
Amazon Textract
Parsio.io
Micronaut Framework DocParserBased on our record, Micronaut Framework should be more popular than DocParser. It has been mentiond 49 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.
Reduce memory-heavy dependencies. Third party libraries are often very resource-hungry. Opt for lightweight lambda-friendly frameworks such as Micronaut or Quarkus. - Source: dev.to / about 2 months ago
The innovations didn't stop there. We also use compilation to a native image via GraalVM, which enabled us to switch to the latest Java versions. Also, we use DI based on Micronaut, and overall, we try to keep up with new industry trends. - Source: dev.to / 3 months ago
This allows Java to have such goodies as reflection, dynamic proxies, ServiceLoader, and DI frameworks like Spring, Micronaut, or Quarkus. - Source: dev.to / 4 months ago
Micronaut is a modern, JVM-based, full-stack framework designed for building modular, highly testable microservices and serverless applications. After working with Micronaut for over two years, I decided to transition to Quarkus. - Source: dev.to / 8 months ago
In this application, we will create products and retrieve them by their ID and use Amazon DynamoDB as a NoSQL database for the persistence layer. We use Amazon API Gateway which makes it easy for developers to create, publish, maintain, monitor and secure APIs and AWS Lambda to execute code without the need to provision or manage servers. We also use AWS SAM, which provides a short syntax optimised for defining... - Source: dev.to / 12 months ago
You could try an online service like https://extract-io.web.app/ or https://docparser.com/. Source: about 3 years ago
DocParser: DocParser simplifies the extraction of structured data from various file formats, such as PDFs and scanned documents, directly into Google Sheets. By automating this process, DocParser saves valuable time and effort otherwise spent on manual data entry. Link to DocParser. Source: about 3 years ago
There are several tools available today that can help you extract tables from PDF files (such as Tabula), or even parse PDFs into structured JSON using AI (like Parsio -> I'm the founder) or without AI (like Docparser). Source: over 3 years ago
Thank you for sharing those! I didn't know them I've only checked this one https://docparser.com/ and I think my solution could be better because it will be easier for the user. Source: over 3 years ago
As previously suggested, if the layout of your PDFs never changes (consistent column widths in tables and placement), you can use a zonal PDF parser like DocParser. Alternatively, an AI-powered parser may be a better choice. Source: over 3 years ago
vert.x - From Wikipedia, the free encyclopedia
Nanonets - Worlds best image recognition, object detection and OCR APIs. NanoNetsโ platform makes it straightforward and fast to create highly accurate Deep Learning models.
helidon - Helidon Project, Java libraries crafted for Microservices
Parseur.com - Automate text extraction from emails and PDFs by using our powerful email and document parser.
Javalin - Simple REST APIs for Java and Kotlin
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.