Artificial intelligence and machine learning have long been a part of everyday life. FaceID, Internet search, tools like Grammarly for spell checking, Alexa and Siri, Smart Home systems, and much more — all of these work with the help of AI.

Artificial intelligence is being actively implemented in many services and in different variations. These include elements of computer vision, natural language processing, and machine hearing.

To develop and prototype solutions using artificial intelligence and machine learning technologies, it is often necessary to be proficient in Python, Tensorflow, Keras, and PyTorch, which require programming skills. However, a number of so-called no-code tools have appeared, with the help of which you can visually train and test AI algorithms.

Diversido has long noticed that low-code/no-code and artificial intelligence go hand in hand. Zero-coding platforms help businesses save on analyst staff by offering automated machine-learning models and a number of other benefits.

Let’s investigate all of them together!

No Code

How No Code Development Works

Low-code and no-code platforms are closely related to PaaS (platform as a service), which offers hardware and software services in the form of cloud services. aPaas (application platform as a service) platforms provide the highest level of abstraction. Thus, developers can model apps rather than code them without worrying about the OS, storage, infrastructure, updates, etc.

Low-code and no-code offer the solution to develop apps without much coding skills. Users get access to a visual development environment and can select the desired functional elements from the library, connect them visually into a workflow, usually by dragging boxes on the screen, thus creating their own applications.

Simply put, you visually do what a developer usually writes in code. In low-code applications, you need a minimum of code. In the case of no-code, you use pre-installed templates and models without using any code at all.

Apps That Can Be Built with No Code

There are many no-code use cases. It is not limited to just creating websites. Some of the most prominent examples include:

  • mobile apps;
  • web apps;
  • voice apps;
  • back-end tools;
  • Integrations;
  • task automation.

The pandemic has shown that even a classic offline business needs IT products: from a simple website to internal accounting systems, CRM, mobile, and web applications that optimize routine business processes and help expand coverage through a multi-million online audience.

Against the backdrop of growing demand for IT products, no-code is beneficial for businesses in that it saves time. Instead of six months, it will take several weeks to make an application or website. And the cost of a traditional digital product ($40,000+) – in the case of using the no-code, decreases many times.

On the other hand, full-code apps allow for complex customizations that can’t be done with no code solutions.

No Code AI

What Problems No Code AI Can Solve

The combination of AI and no-code is beneficial for small and medium businesses. They allow companies to develop custom applications and integrate AI elements into them through third-party APIs. These software innovations make it easy for non-techie employees to get started with AI technologies and help startups get production-ready status.

Quickly Adapts to a Company’s Needs

The problem with traditional hand coding is that it’s impossible to instantly change functionality, especially without a deep knowledge of the programming language you’re looking for. In a no-code AI application, it is enough to simply implement new logic, and the changes will be launched within a few hours.

Automate Repetitive, Monotonous Processes

As per Statista, AI is aiding productivity. Such solutions can be designed to help workers complete manual, repetitive, and routine tasks that were previously performed manually. Through these technologies — especially using machine learning — the developed tool must learn to tune and improve the process flow to create an intelligent process. Also, it can learn and improve over time.

Minimizes Human Involvement

At its core, AI is the simulation of human intelligence processes by machines, especially computer systems. Therefore, AI can be used to analyze data faster than humans, recognizing patterns and learning from past experiences.

By introducing this technology, we not only improve the quality of work but also reduce processing errors. Eliminating the human factor in a number of areas, we get a reduction in operating costs and processing time.

The Industries Where No Code AI Can Be Useful

No-code AI platforms are best suited for businesses that need efficient, turnkey solutions. They are ideal for solving tasks at the level of a specific department, such as sales, finance, or human resources, and can be used effectively for complex projects.

According to, the no-code AI platform market estimated size is $3 billion. And that’s unsurprising since such tools as Amazon SageMaker, Apple CreateML, Google AutoML, Google Teachable Machine, and Microsoft Lobe are already making wind in many spheres.

Artificial intelligence in marketing

For example, Siemens Mobility has tested a prototype no-code AI monitoring system through traffic cameras. The BMW Group has been using automatic image recognition for quality and pseudo-defect checks to ensure that there is no deviation from the target, despite the absence of real faults.

No Code Development and AI — a Future or a New Reality?

Artificial intelligence does what was previously deemed impossible: it assists in quick decision-making and reduces choices by suggesting the right solutions. Indeed, in traditional development, to implement business logic, you need to perform a number of routine tasks, which a machine can actually do (if it “understands” the business task).

In fact, AI does the “rough” work, leaving creative tasks for humans. This gives low-code/ no-code an extra boost, allowing them to evolve very quickly.

It’s hard to controvert the value and possibilities of no-code development, especially when it comes to building simple applications.

After all, as Chris Wanstrath, GitHub CEO, said: “The future of coding is no code at all.”

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