GitHub Pages
Vercel
Jekyll
Netlify
Neocities
surge.sh
GitHub
Hugo
DocParser
Amazon Textract
FlexiCapture
Docsumo
Parseur.com
IBM Datacap
Workfusion Intelligent Automation Cloud
ABBYY FineReader
GitHub Pages DocParserBased on our record, GitHub Pages seems to be a lot more popular than DocParser. While we know about 468 links to GitHub Pages, 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.
I moved my blog from WordPress to GitLab Pages in... 2016. I'm happy with the solution. However, I used GitHub Pages when I was teaching for both the courses and the exercises, e.g., Java EE. At the time, there was no GitHub Actions: I used Travis CI to build and deploy. - Source: dev.to / 12 days ago
You can deploy to Github Pages in under 2 minutes by following their documentation. - Source: dev.to / about 2 months ago
For this application, Elm controlled the routing. So, I had to adapt the scripts to deploy to Netlify instead of GitHub Pages. Why? Because you need to be able to tell the web server to redirect all relevant requests to the application. GitHub Pages doesn't have support for it. - Source: dev.to / 2 months ago
It's super easy to publish a static site like the resume with GitHub Pages. Just check out the docs. - Source: dev.to / 3 months ago
GitHub Pages: Host your static websites directly from your GitHub repository. - Source: dev.to / 4 months ago
You could try an online service like https://extract-io.web.app/ or https://docparser.com/. Source: about 1 year 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 1 year 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: about 1 year 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 1 year 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 1 year ago
Vercel - Vercel is the platform for frontend developers, providing the speed and reliability innovators need to create at the moment of inspiration.
Amazon Textract - Easily extract text and data from virtually any document using Amazon Textract. Textract goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables.
Jekyll - Jekyll is a simple, blog aware, static site generator.
FlexiCapture - ABBYY FlexiCapture brings together the best NLP, machine learning, and advanced recognition capabilities into a single, enterprise-scale platform to handle every type of document. Available in the Cloud, on premise or as SDK.
Netlify - Build, deploy and host your static site or app with a drag and drop interface and automatic delpoys from GitHub or Bitbucket
Docsumo - Extract Data from Unstructured Documents - Easily. Efficiently. Accurately.