Mock sample for your project: PDF Blocks API

The powerful Optical Character Recognition (OCR) APIs let you convert scanned images of pages into recognized text.

For more information on how to use these APIs, including how to create an API key required for authentication, see Alma REST APIs.

The general-purpose API

ADVICEment's DynamicDocs API automates your document generation and creates dynamic, optimized, interactive PDFs. Write your templates in LaTeX and call the API with JSON data to get your PDFs in seconds.
The template files are stored in your dashboard and can be edited, tested and published online. Document templates can contain dynamic text using logic statements, include tables stretching multiple pages and show great-looking charts based on the underlying data. LaTeX creates crisp, high-quality documents where every detail is well-positioned and styled.
Integrate with ADVICEment DynamicDocs API in minutes and start creating beautiful dynamic PDF documents for your needs.
For more information, visit DynamicDocs API Home page.

Fungenerators taunt generation API generates random taunts / insults, relevant to the given category. Many categories are supported and new ones are added very frequently. Click here to subscribe

The current api version is v3.4 The api methods listed below can be called directly from this page to test the output. You might set the api_key to pre-authenticate all requests on this page (this will work if your secret is blank). API endpoint URL: http://{apiName}.text2data.com/v3/ {method} The api can be consumed directly or using our SDK. Our Excel Add-In and Google Sheets Add-on are also using this api to process the data.

Fungenerators name generation API generates random names relevant to the given category. Lots of categories are supported with many variations supported. Click here to subscribe

A full featured, REST based UUID generator with json/xml/jsonp result support. You can try them out right here. Click here to subscribe

NamSor API v2 : enpoints to process personal names (gender, cultural origin or ethnicity) in all alphabets or languages. By default, enpoints use 1 unit per name (ex. Gender), but Ethnicity classification uses 10 to 20 units per name depending on taxonomy. Use GET methods for small tests, but prefer POST methods for higher throughput (batch processing of up to 100 names at a time). Need something you can't find here? We have many more features coming soon. Let us know, we'll do our best to add it!

Semantria applies Text and Sentiment Analysis to tweets, facebook posts, surveys, reviews or enterprise content.