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Top no-code AI Platforms

With the evolution of no-code AI, sectors such as web development are advancing while others are just emerging. Now, with these no-code AI platforms, businesses have a chance to explore the technology without needing to hire tech experts or adopting expensive strategies. 

With the evolution of technology, it is now possible to design complicated apps without investing a lot of money, waiting months or years, or hiring several developers.

No-code platforms have made it easy to create programs that use advanced technologies. The introduction of these platforms has resulted in an increasing number of businesses attempting to use their capacity to build AI solutions.
With this, visual drag-and-drop tools come into the picture, aiding data scientists in filling the void and making AI less daunting for people with non-technical backgrounds.

This article discusses the top no-code platforms for building AI solutions.


Clarifai, founded in 2013, is an NLP and Computer Vision tool that provides an end-to-end solution for modeling unstructured data throughout the AI lifecycle. Image, text, and video recognition solutions are built on a cutting-edge machine learning platform that can be accessed through API, device SDK, or on-premise. They have some neat pre-trained models on offer and boast precise and thorough findings with a fast API.


Apple has been allowing developers to use transfer learning to create bespoke machine learning models since 2018. The app enables users to create models for object and activity detection, as well as picture, sound, video, text, and tabular models. Create ML makes use of the machine learning infrastructure embedded into Apple products like Photos and Siri, and it also allows for custom data training and the simultaneous training of many models using various datasets.

Google AutoML

AutoML is the Google package star, which works like CreateML but in the cloud. Sight (Vision and Video Intelligence, the latter in beta) and Language (NLP & Translation), as well as structured data functions (Tables), are currently included in the model package. Overall, AutoML manages to deal with much information in no-code, but it is difficult to operationalize if you are not a developer.


The DataRobot enterprise AI platform modifies data science and automates the whole AI development, deployment, and maintenance process. It was founded in 2012, focusing on predictive models, powered by open-source algorithms, and offered in the cloud, on-premise, or as a fully-managed AI service.


Levity focuses on text, image, and document categorization and allows users to train unique models on their use-case-specific data, and is suitable for companies of all sizes. A human-in-the-loop option is included in custom models and processes, giving users complete control over the model, which requests inputs when it is unsure and learns from interactions. Levity focuses on offering a solution that integrates with all the tools that people use every day.


Lobe, a Microsoft tool, can classify images and recognize objects, with data classification coming soon. Lobe is a private, free desktop application with a large number of pre-trained solutions (e.g. Emotional Reactions which lets your app react to various expressions letting people send emoji reactions just through their faces).


MakeML is a developer tool for developing object recognition and segmentation models, founded in 2018. They have some excellent instructions on recognizing a variety of touch-points for various activities. MakeML includes a dataset store with many free alternatives, as well as the ability for platform users to sell and buy datasets.


Obviously AI, created in 2019, uses natural language processing to perform tasks on user-specific text data. Drag and drop your data as a CSV file or integrate with HubSpot, Salesforce, or MySQL (among others), select your prediction field, and it will generate a custom machine learning model and a prediction report for you. The platform is particularly beneficial to SMEs searching for a tool that selects the best algorithm for their needs.


MonkeyLearn is an all-in-one text analysis and data visualization studio that can be used to extract topic, sentiment, intent, keywords, and other information from unstructured text-based data. Automatically tagging business data, presenting actionable insights and trends, and simplifying text classification and extraction processes are just a few of the features. It integrates with Zendesk, RapidMinder, and Google products, with a few others on the way. Also, it is one of the best blog resources for text analysis.


RunwayML is a tool for creators that focuses on creative work that involves dealing with pictures, videos, text, latent spaces, and segmentation masks, as well as motion capture, backdrop removal, and style transfer. They have a Generative Engine, which is a storytelling machine that generates visuals automatically as you write.


Businesses are increasingly turning to no-code platforms for a variety of reasons. Access to developers and software engineers slows project delivery, partly owing to the ripple impact on workforce management, and this is where technology can help. The unicorn we all want to catch is not only enabling your team to create solutions but also being relevant and competitive in the present context.

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