A semantic personal publishing platform with a focus on aesthetics, web standards, and usability.
It is a no-code platform designed to help businesses create production-level applications with code generation: backend, web, and native mobile apps. With this tool, you can grow from an MVP to an enterprise solution with millions of requests per minute, while having total control over where you deploy your application, and remaining independent from the platform with source code exports. | It is an open-source no-code system for text annotation and building text classifiers. With this, domain experts can quickly create custom Natural Language Processing (NLP) models by themselves, with no dependency on NLP experts. No AI knowledge needed; from task definition to working model in just a few hours! |
Design relational databases in PostgreSQL-compatible format with total flexibility in a visual designer;
Manage complex business logic with hundreds of functions and an intuitive drag & drop interface;
Create and manage access to your API and configure your endpoints with middleware, automatically generate API documentation;
Build web dashboards in minutes with auto-generated pages and prebuilt components;
Design native mobile applications for iOS & Android, and publish them to Google Play & App Store;
Deploy your application in clusters to the AppMaster.io cloud, AWS, Azure, Google Cloud, or a local server, and export the binaries & source code at any moment;
Power up your app and connect it with your favorite tools with modules (authorization, email, SMS, Stripe, Telegram, AWS, Slack, Zoom, and dozens of others); | Extensible architecture;
Open source;
No AI knowledge needed;
From task definition to working model in just a few hours |
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GitHub Stars - | GitHub Stars 269 |
GitHub Forks - | GitHub Forks 41 |
Stacks 2 | Stacks 0 |
Followers 4 | Followers 3 |
Votes 0 | Votes 0 |
Integrations | |

rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.

It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.

It is a visual programming language that lets you build a fully-functional web app without writing code. Users have built marketplaces, CRM tools, social networks. Engineers can focus on new features and add them as plugins with code, while business people can focus on the customer-facing product.

It can be used to complement any regular touch user interface with a real time voice user interface. It offers real time feedback for faster and more intuitive experience that enables end user to recover from possible errors quickly and with no interruptions.

Power websites, apps, or whatever you like, all from a spreadsheet. Changes to your spreadsheet update your API in realtime.

Create, customize, launch, and iterate on your mobile app, all from your browser. Source code included.

Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.

It is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.

It provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks.

It is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices.