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The 10 Best Examples of Low-Code and No-Code AI Platforms

No-Code and Low-Code AI Platforms

Artificial intelligence (AI) can transform any business from providing customers with intelligent products and services to streamlining internal processes.

However, the barriers to entry, from investment and infrastructure to training and recruiting a skilled workforce, can seem intimidating. That is why no-code and low-code AI platforms are so exciting. They allow anyone to use AI without the need to write technical code. Using No-code and Low-code platforms, anyone can dive in and start creating innovative applications that leverage machine learning; from designing web services to customer-facing applications to coordinating sales and marketing campaigns, they are more accessible than ever to get started with AI. No-code and Low-code solutions typically operate in one of two ways either by a drag-and-drop interface where users simply choose the elements they want to include in their applications and then put them together using a visual user interface or through a wizard where users answer questions and select options from drop-down menus.   

What is No-Code?        

No-code AI is a code-free technology that enables non-AI experts to implement and test their ideas without any AI experts. No-code enables non-technical users to quickly classify and analyze data and easily build accurate models to make predictions without business analysts.

What is Low-Code?

Low code is a rapid application development technique with visual tools, point clicks, and drag and drop. But also allows us to do some coding and scripting.  Low code will enable developers of mixed experience levels and backgrounds to develop applications for web and mobile by using drag-and-drop components and model-driven logic. Low-code platform enables business users to create apps without writing code. Professional developers enjoy flexibility.  

Examples of Low-Code and No-Code AI Platforms

Google Cloud AutoML

We need AI technology for image analysis that is easily accessible for enterprises. So, Google Cloud Platform has created Cloud AutoML vision. To perform image analysis on the Google Cloud Platform, developers can use the vision API to access a pre-trained model or design and train a custom model with Cloud Machine Learning Engine. CAML vision lets businesses and developers with limited machine learning expertise train custom vision. 

Microsoft Azure ML

  • Azure Machine Learning is a cloud base service that helps to manage and accelerate machine learning projects.  
  • Azure machine learning is also known as “Azure ML.”
  • Visual UI like Visio
  • Drag-and-drop machine learning, No terminal, command line, and code.
  • Advance data mining integration: R, Python, SQL.
  • Deployment integration with RESTful API, C#, R, and Python.
  • The best tool to learn machine learning. 
  • Azure Machine Learning Studio is a service within the Azure cloud ecosystem.

IBM Watson Studio

IBM Waston Studion is a data science IDE that will allow data scientists, business analysts data engineers to collaborate on data science projects. IBM Waston machine learning is an area in which users can produce or operationalize their machine learning models that were developed. It is a new kind of computing and very different from programmable systems.

Amazon SageMaker

Amazon SageMaker helps data scientists and developers t prepare data and build, train, and deploy machine learning models quickly by bringing together purpose-built capabilities. Their capabilities allow us to build highly accurate models that improve over time without all the undifferentiated heavy lifting of managing ML environments and infrastructure.  

SageMaker helps to develop great machine-learning models.

It allows users to connect and load data from different sources, such as Amazon, S3, and Amazon Redshift, in just a few clicks. 


DataRobot is the only trusted AI platform that automates and accelerates every step of your journey from data to value. It is truly open to all users. DataRobot debuted furthest to the right for “Completeness of vision” on the latest Gartner Magic Quadrant for data science and machine learning platform.

DataRobot sets the standard for augmented data science and ML.  


Mendix is a leader in application development, meeting head on the need to deliver software differently. It’s a low-code application development platform from Siemens digital industries software that enables industrial organizations to jumpstart digitalization across products and processes. It includes four foundational components to deliver a unique blend of development Application Development Platforms: Agility, digital capabilities, and personalized experiences.

Low Code Development:  It is a game-changing environment enabling anyone, from most seasoned developers to engineers and key business professionals, to build sophisticated, high-value applications. 

Application Services:  Through app services, users can use these flexible building blocks to create new industrial apps or extend existing ones.

Data and Integration Services: We make it easy to access and integrate data from any source, any system, and any data set from Mendix to the user’s ERP and CRM system. 


The H2O.ai platform offers one deep net -the multiplayer perception and a few other machine learning algorithms. H2O started as an open-source machine learning platform, with deep nets being a recent addition. Besides machine learning algorithms, the platform offers several useful features, such as data pre-processing. Currently, the only deep net supported by H2O is the multilayer perception.  H2O has built-in integration tools for platforms like HDFS, Amazon S3, SQL, and NoSQL. 

It is a downloadable software package that users must deploy and manage on personal hardware infrastructure.   


The OutSystems is a low code development platform that allows organizations to build, deploy, and manage web and mobile applications. It is a popular low-code development platform unknown for its ability to help businesses quickly custom web and mobile applications with minimal coding. It enables users to create custom applications through a visual drag-and-drop interface without extensive coding knowledge.

OutSystems offers a variety of pre-built templates, modules, and components that can be easily customized to suit specific business needs. It is used by businesses across industries, including banking, healthcare, and manufacturing.

Some reasons why OutSystems is popular among businesses and developers include

Rapid Application Development: OutSystems allows developers to create applications up to 10 times faster than traditional development methods by using its visual development interface, pre-built components, and easy-to-use workflows. 

Low-code Platform: OutSystems uses a low-code approach to development, meaning that users can build complex applications without writing a lot of code. This makes it easier for businesses to create custom applications with their existing IT staff and resources.    

Scalability: Its applications are designed to be highly scalable, meaning they can grow and adapt to changing business needs over time. This scalability is achieved through modular architecture, cloud deployment options, and integrations with other systems.  


It is a no-code platform that is very similar to Bubble but is built in its own way with unique strengths and weaknesses. It enables users to build apps for all different purposes for mobile, desktop, TV, etc.    


It is another no-code development platform offering features similar to Nintex and Visual Studio Creator. It’s an American software company to develop software for customer relationship management, digital process automation, and business process management. The Pega software mainly helps in the security systems that it provides.   

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