
GraphQL
Next.js
React
gRPC
Nest.js
Hasura
Strapi
ExpressJS
DocParser
Nanonets
Parseur.com
Rossum
Docsumo
DocuClipper
Parsio.io
FlexiCapture
GraphQL
DocParserBased on our record, GraphQL seems to be a lot more popular than DocParser. While we know about 258 links to GraphQL, we've tracked only 14 mentions of DocParser. 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.
GraphQL is a query language combined with a server-side runtime. It was created by Facebook in 2012, and soon after, they released the specification to the public and made a NodeJS implementation open source. - Source: dev.to / 4 months ago
Definitely they should include D4M and GraphQL [1],[2]. Not only D4M can cater for structured relational data, it also suitable for sparse data in spreadsheet, matrices and graph. It's essentially a generalization of SQL but for all things data. There's also integration of D4M with SciDB [3]. [1] D4M: Dynamic Distributed Dimensional Data Model: https://d4m.mit.edu/ [2] GraphQL: https://graphql.org/ [3] D4M:... - Source: Hacker News / 8 months ago
GraphQL is becoming a popular choice, making development easier. - Source: dev.to / 10 months ago
In modern software architecture, Jamstack separates the frontend from the backend through API consumption. Traditionally, this has been achieved with RESTful APIs, which enable data exchange between server and client. However, REST often causes performance issues, such as over-fetching and added complexity. A client may need only a small subset of data, but a REST endpoint might return an entire dataset, which... - Source: dev.to / 11 months ago
Before we dive into GraphQL, it's crucial to understand the challenges it was designed to solve. Traditional API architectures like REST often struggle with two pervasive and inefficient patterns:. - Source: dev.to / 11 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
Next.js - A small framework for server-rendered universal JavaScript apps
Nanonets - Worlds best image recognition, object detection and OCR APIs. NanoNetsโ platform makes it straightforward and fast to create highly accurate Deep Learning models.
React - A JavaScript library for building user interfaces
Parseur.com - Automate text extraction from emails and PDFs by using our powerful email and document parser.
gRPC - Application and Data, Languages & Frameworks, Remote Procedure Call (RPC), and Service Discovery
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.