How Low-code AI is Changing the Tech Landscape & Drive Results

While AI is still making noises with its ability to perform manual work, analyze data and predict the next trends, another “newcomer”– low-code – has also integrated with AI for better process automation and analytics. A drag-and-drop development tool with AI features seems ideal for developers and businesses.

What Is Low-code AI?

Using low-code AI, you can quickly build AI applications without extensive coding and technical (programming + machine learning) knowledge.

How? Well, thanks to the pre-built code blocks, you can drag them into places to assemble an application and might even reuse them for upcoming projects. From there, even users with less knowledge of technology can take part in creating AI systems after a few quick training sessions.

Traditional coding is needed when you want to add customization. By cutting down time for groundwork, the overall development time is shortened, and developers can focus more on challenging technical aspects.

Why Should I Consider Low-Code AI?

First, low-code AI platforms provide a broad array of functionalities tied to AI and machine learning technologies. While many low-code solutions said they support AI application development, their capabilities often extend only to fundamental aspects. For more intricate projects, opting for a specialized Low-Code AI platform is better, as it simplifies the creation, maintenance, and enhancement of your application.

Furthermore, certain low-code AI platforms feature AI assistants that can enhance software development workflows by offering code suggestions during customization. While these recommendations may not always be accurate, having them can be beneficial for streamlining the development process.

There’s no limitation to the ideal customer profile of Low-code AI. Businesses of all sizes and from any industry can utilize this emerging tool.

However, low-code AI is the best for data-driven use cases such as marketing, sales, finance, manufacturing, securities and insurance. For example, you can build an AI system that predicts churn rates and analyzes data from reports. For automation, it can help humans in mundane tasks such as invoicing.

Best Low-Code AI Platforms

The market is flooded with various low-code platforms, yet it's crucial to identify those that offer distinctive functional capabilities specifically suited for developing AI applications.

Here are our top choices:

SuperAnnote: Best for large databases. It can annotate, manage, and version ground truth data for a custom AI model with a full-fledged toolset and powerful data management. From there, you can easily orchestrate your AI pipeline and extract meaningful insights.

Obviously AI: You can set up machine learning algorithms based on your business process without any coding. Then let it automatically run and operate. Due to this, the platform is suitable for anyone from any background.

Genexus: This low-code enterprise platform employs artificial intelligence to automate and maintain applications. To make it happen, Genexus leverages Generate AI for code generation. It will constantly suggest new lines of code, hence you will save development time and increase accuracy.

Pega: To assist you through decision-making with accuracy, this powerful tool offers data mining, predictive analytics and event processing features.

DataRobot: This cloud-based solution offers automated data preparation, algorithm development, and deployment features. It comes with specialized models tailored for sectors such as finance, retail, healthcare, manufacturing, and government agencies.

Nanonets: Focusing on computer vision and streamlining the process of extracting structured or semi-structured data from various documents, this tool is ideal for businesses looking to reduce the costs and inefficiencies associated with data importation from forms and textual content.

Akkio: Akkio allows for the swift deployment of AI solutions, requiring no coding or data science background. Users can easily create and test AI-driven workflows, benefiting from strong integration capabilities.

PyCaret: Being a Python library, it might need a bit more technical skill than some other options, it's still regarded as low-code due to its array of pre-set functions and wrappers that simplify data management, analysis, and model training.

Lobe: Lobe is an intuitive tool for training image recognition algorithms. It's designed for beginners, automatically choosing the most effective models for the task at hand. Users can easily transition to Azure AI for more complex machine learning projects without any coding requirement.

Teachable Machine: This platform offers easy-to-follow tutorials for training algorithms in basic data classification and categorization, key applications of machine learning and AI. Its highlight is the educational tool, which is excellent for learning the basics of AI.

Thinking about using Low-code AI for your digital transformation? Synodus is a Qualified Low-code Developer service provider with years of experience in software development. Having worked with businesses across the spectrum, we utilized low-code to build all types of applications, from AI to non-AI such as workflow automation, internal tools, CRM, ERP and many more!

A team of 250+ experts are ready for our next journey!