Top 20 No-Code AI Tools for 2022
No-Code AI is the future of AI Democratization
At the last TechCrunch Sessions SAAS, Databricks CEO Ali Ghodsi alluded that No-Code AI would be the future of AI due to shortages of Artificial Intelligence (AI) experts compared to the staggering demand for effective and actionable enterprise AI. The same oppinion has also been echoed by leaders of many tech companies such as Microsoft, Google and Amazon.
The enormous interest to easily engrain enterprise AI into business or technical or scientific processes does not only stems from small and midsize companies, but also big organizations. This has the potential to profoundly enhance performance or sink cost. Such companies come from a wide variety of industries. For instance, sales reps need fast tangible insights from data to make data-driven business decisions and close sales opportunities faster. Marketing executives are seeking information on how to best hyper target customers using both their data and social network datasets. In health care, physicians are eager to try new AI tools for early disease diagnoses in order to uncover new disease patterns, which cannot be seen with human eyes and cannot be captured by existing rule-based diagnostic software. Injecting AI could be imperative for biotechnology — where scientists are overwhelmed with a staggering number of protein or molecular combinations that they have to choose from to identify a good match during drug discovery. The same is true for industry 4.0, where there is an urge and rush by engineers to use AI for process mining and optimization to save cost.
We have witnessed for over a decade how Big Tech companies have relentlessly and successfully used AI to discover new businesses, enhanced product differentiation and disrupt incumbent competitors. Small, medium size companies, as well as big non-tech or tech companies can leverage No-Code AI to close the AI technology gaps in the above-mentioned industries (i.e., sales, marketing, health care, industry 4.0 etc.). This would significantly improve their clout with existing customers, defend their market positions, hone current business models and expose new product differentiation approaches to standout from competitors.
In this post, we present a range of top No-Code AI tools that can be used by small, medium size and big companies that are weary to build an AI team but intend to deeply incorporate AI in their enterprises.
What is No-Code AI
Simply put, No-Code AI is the democratization of AI to enable anybody with even no knowledge of machine learning to build and run AI models without writing a single line of code.
What is Low-Code AI
Low-Code AI presents a user with a user interface to build and run machine learning pipelines with a small amount of code. Low-Code AI tools can also be used by data scientists, as well as technical users with basic knowledge of coding.
What is AutoML
AutoML is the ability of a machine learning system to solve a machine learning problem by searching the optimal sequence of machine learning models and their corresponding hyper parameters.
Survey of Top No-Code AI tools for 2022
The focus of several No-Code/Low-Code AI surveys have solely been based on the clustering of No-Code AI systems according to their machine learning verticals, such as NLP, Computer Vision, Speech, Time Series. However, numerous real-world machine learning problems usually involve a union of two or more of these machine learning verticals. For instance, a typical machine learning problem may be to combine customer calls (i.e., speech) with historical emails (Text — NLP) and data from CRM (tabular data) to predict the next move of a customer. Based on these, our survey of No-Code AI solutions additionally cluster the No-Code AI tools with respect to their product market verticals (e.g. Sales, Health Care). Figure 1.0 depicts are survey for No-Code AI solutions for 2022.
In what follows, we present the top No-Code AI tools, explain theircapabilities and in some cases describe the underlying technologies that powers the No-Code AI tools.
Description and Analysis of No-Code AI Solutions
Google Cloud AutoML Vision
Google Cloud AutoML has the capability to train complex machine learning tasks such as image recognition without writing a single line of code. The underlying technology utilizes massive amount of transfer learning and intelligent neural architecture search to execute AutoML tasks.
Underlying AI Technology: Google AutoML use of neural architecture search has given its No-Code AI tool superiority over many AutoML tools in the market. Another advanced No-Code AI tool that also leverages neural architecture search is the Evercot AI No-Code AI tool. These No-Code AI tools can solve very complex machine learning problems and can also be used by data scientists. Complex AutoML demands lots of computational power. A trade-off has to be made between computing time, cost and the acceptable accuracy of the AutoML result.
Teachable Machine
Presents users an opportunity to train and use machine learning models for their applications without writing codes. The training approach is so easy and seamless such that anyone can simply create an object detection app. All that is required from the user is to perform an action (image/audio), label the action using the Teachable Machine browser GUI. The user can then click the start training button on the drag and drop user interface to commence training. Immediately as the training is over, the model can be utilized in an application or exported to a third-party app.
Underlying AI Technology: To successfully accomplish all the image and text recognition tasks performed by Teachable Machines, they use stored weights of well-trained neural networks and combine them with the new weights of image/text provided by the user. This process is called Transfer Learning and leads to the generation of enhanced image/text recognition results with little training.
Evercot AI
Their No-Code AI tool provides an easy to use drag and drop user interface, which can be used to run both simple and very complex AI tasks without writing a single line of code. The Evercot AI No-code tool is widely used by sales and marketing executives to perform sales opportunity scorings and predictions with data from CRM such as sales force and snowflake. The tool also strongly focuses on No-Code AI diagnostics in Health Care.
Moreover, their No-Code AI platform is capable of using AutoML if desired to solve machine learning problems by simply combining data to their AutoML engine through drag and drop to obtain enhanced autonomous AI results. The Evercot AI No-Code platform provides advanced users a GUI to configure the architecture and layers of their neural networks of any complexity during deep learning.
Underlying AI Technology: Most No-Code AI tools rely on solely on deep learning that is based on Remembering historical patterns. The Evercot AI No-Code AI tool clearly stands-out from other No-Code AI tools because it has developed an enhanced type of proprietary AI technology which Thinks instead of solely Remembering. Among others, the Evercot AI No-Code tool combines this proprietary AI technology with Neural Architectural Search to power its AutoML module to creatively think like humans — on how to autonomously and optimally react to build ML pipelines on new situations that have never been encountered before. This translates into the synthesis of complex and superior AutoML pipelines that deliver enhanced AI results for very complex machine learning tasks.
The backend of their Node-Code AI platform also utilizes the vast variety of standard publicly available machine algorithms for classification, regression, clustering, reinforcement learning and outlier detection tasks. For deep learning tasks, in case the user does not have large amounts of historical data, Evercot AI No-Code tool applies transfer learning to obtain good AI results with little data.
DataRobot
DataRobot: has a No-Code AI App builder that enables non-technical and technical users to build rich AI applications without coding. Users are offered a drag and drop user interface, which can be configured to run and produce machine learning results in minutes. In addition, what-if scenarios can also be configured.
Underlying AI Technology: For several years, DataRobot provides a holistic AI platform that addresses AI problems in a vast spectrum of fields fluctuating from sales to engineering. Their No-Code AI platform leverages these existing algorithms, which range from supervised learning (e.g., classification, prediction) to unsupervised learning (clustering, outlier detection).
Lobe
Presents a user interface where users can input an image or a burst of images using a camera. The system then automatically detects and classifies the human activity. No code is required by the user. In particular, once an image is added, training commences automatically without the submission of any parameter. The backend then provides the classification activity results. In cases where the system inaccurately predicts an event or activity, Lobe provides a GUI for the user to enter a feedback to notify the system of the misclassification error. In this manner, the system would automatically retrain the model and ensure that future predictions are improved. An interesting feature provided by Lobe is the ability to export the model to different formats such as TensorFlow and CoreML IoS App. Lobe is a desktop application.
Technology Underneath: After the acquisition of Lobe by Microsoft, the machine learning models offered by Lobe are now also tapping into decades of AI knowledge amassed at Microsoft.
Create ML
CreateML is a No-Code AI platform provided by Apple that allows users to use a drag and drop user interface to perform an AI task such as image classification. The image classification is based on an approach called transfer learning which uses less training data from the user’s historical data.
CreateML provides an array of pre-trained model templates. These templates enable users to quickly build custom models through the utilization of transfer learning. In addition, the tool provides a wide range of AI functionalities ranging from image classifiers through Natural Language Processing (NLP) to recommendation systems.
RunwayML
RunwayML offers users a No-Code AI tool that has the capability to automatically generate and synthesize images and text using Generative Adversarial Networks (GAN) without writing a piece of code. In addition, it provides users the ability to detect objects in video and images. Also, it can be used for video editing.
Clarifai
Provides a machine learning tool that runs numerous computer vision tasks such as data labeling, object detection, image recognition etc. Specifically, it provides pretrained machine learning models that a user can leverage to solve a given custom task. Based on this, the user can create a so called “concept” to run the pre-trained model on their data. Users are presented a tab-based UI or a drag and drop UI to carry out this activity. The machine learning algorithms run at the backend with no coding by the user. Once the task finishes, the outputted results are displayed in multiple formats. Furthermore, users have the ability to call the backend algorithms using API.
ObviouslyAI
Obviously AI provides a No-Code AI tool that enables users to perform machine learning tasks such as sales forecast on tabular data without the writing of codes. The tool also offers users an option to ask questions to the system. Once questions are received, their backend machine learning utilizes NLP to interpret the questions and subsequently perform prediction based on the submitted questions.
MonkeyLearn
Is an NLP No-Code AI tool that provides a GUI to help users to capture and classify massive volumes of text based on a topic or user intent. The tool also has the capability to evaluate sentiments. Machine learning results produced by the system can be exported to other external systems.
NanoNet
Similar to MonkeyLearn, NanoNet provides a document classification NLP No-Code AI solution. The NanoNet tool computes and separates huge amount of heterogenous documents stemming from multiple data sources such as emails and customer support systems.
Levity
Levity offers a No-Code AI tool that enables users to accomplish document, text and image machine learning tasks without writing a single line of code. Their tool provides an easy to use user interface and features that enable users to automate several document related tasks.
Akkio
Akkio provides a No-Code AI platform that is geared towards enabling business users from marketing, sales and retail to successfully run AI to solve their business problems — without writing codes. In addition, their No-Code AI tool also offers an API for more technical users such as Data Scientists. This can be used to easily deploy AI applications without the need of software engineers. The machine learning technologies of Akkio provide solutions to a wide variety of tasks such as churn reduction, text classification and customer LTV prediction.
Skyl.ai
Skyl provides a general-purpose No-Code AI platform that gives users the ability to run a vast variety of machine learning tasks ranging from audio, text and image recognition without coding. Their platform is designed to cover machine learning use cases from a broad array of industries ranging from transportation, automotive, marketing, insurance through banking to agriculture.
Peltarion
Is a cloud-based No-Code AI platform that provides users the end-to-end capability to run AI from data selection through model selection or building to model deployment on a production system. Its intuitive GUI allows teams to build and share deep-learning models at a granularity whereby even the architecture or layers of a neural network can be customized. After models have been successfully trained the user is provided an API link, which can be used to run the model on real production datasets through the API.
C3 AI Ex Machina
Provides a general-purpose No-Code AI solution that gives users the capability to prepare data and run scalable machine learning models without writing any code. Users have the option to reserve a workspace to store their data on the Ex Machina cloud infrastructure, run any machine learning task, and subsequently scale their operation if required.
Amazon SageMaker
Is a robust cloud-based machine learning platform that provides a No-Code user interface for technical developers to build, train and deploy simple to very complex machine learning models. It offers an easy to use GUI to manage, monitor and re-run current and historical machine learning pipelines. It’s a great tool for data scientists.
ML Jar
Is an automated machine learning tool that focuses on tabular data to enable users to perform AutoML without writing codes. Specifically, its AutoML technology synthesizes pipeline that covers feature engineering, model selection and data visualization.
MakeML
Is a No-Code AI tool that helps software developers to perform object detection using machine learning without writing any code.
H2O.AI
Provides a holistic machine learning platform to build AI models using AutoML and a broad spectrum of publicly existing machine learning libraries. It also offers a easy approach to deploy and manage machine learning models.
