AI Business Solutions

We optimize many routine processes through machine learning and the implementation of artificial intelligence, allowing you to reduce the time for data collection and processing, as well as the cost of manual work.

We help to identify patterns in user behaviour, process large volumes of data, predict, and increase planning accuracy by implementing AI into your business processes.

We unlock new benefits for our customers with image, video, and speech recognition systems, helping them to leave their competitors far behind.

Ranging from the online translator and the presentation generator to the expense auditor and the programming assistant GitHub Copilot, there are many apps available to businesses using artificial intelligence. They make it possible to work faster and more efficiently, completing assignments at a much lower cost.

The use of artificial intelligence in business is the most hotly discussed topic today. Expert findings indicate the widespread use of this technology, especially in the service sector. And surveys of business people prove the value of artificial intelligence: 80% of large companies are investing in the development of this technology.

In 2021, the global artificial intelligence market was estimated at around $87 billion. It’s expected to reach $1.6 trillion by 2030, with a compound annual growth rate of 38.1% from 2022 to 2030:

Artificial intelligence market size

Definition of artificial intelligence

Artificial intelligence (AI) is a field of computer science and a technology for creating software capable of using and analysing data, algorithms, and programming elements to carry out various autonomous actions. Such software is capable of self-learning, predicting, and adapting to changing conditions. In a nutshell, if a machine exhibits human-like cognitive abilities, then it’s considered to possess artificial intelligence.

At present, there are two types of artificial intelligence, based on functions and capabilities:

  1. Narrow AI, or ‘weak’ AI. It is directed to perform one or more specific tasks. This type includes all known apps that use AI, even if they’re based on neural networks or deep learning.
  2. Full AI, or ‘strong’ AI. In theory, it can go beyond learning and extrapolate knowledge for any task. This type doesn’t yet exist, but scientists and developers from IT corporations are already trying to create such almost sentient machines.

Apps with a stated function, that is, those that everyone is already using, are powered by ‘weak’ AI. Although they interact closely with people, find or generate rational answers to any questions, they do this thanks to programmed algorithms. The potential of their ‘intelligence’ is not at a human level because such capabilities aren’t required.

Narrow AI, for instance, works in virtual assistants such as Amazon Alexa, Google Assistant, Cortana by Microsoft, and Siri by Apple. These intelligent software agents parse queries and return appropriate responses or perform desired actions, like finding and ordering products. They don’t possess a mind, unlike people who work as personal assistants for businessmen, but they’re quite capable of coping with their tasks.

Directions in artificial intelligence

Artificial intelligence already imitates people pretty well. This is down to the developers who are trying to develop human abilities in the technology, albeit limited so far. Based on this, directions or disciplines in AI as a field of science have arisen focussing on different abilities.

Machine learning

These are methods of analysing input data that automate the development of an algorithmic model. After learning, the model is trained on additional data sets (gathered data) and improved based on experience, not program code. Compared to an individual, this is the ability to analyse, remember, and solve problems.
Machine learning
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Speech recognition

This is the automatic conversion of a speech signal into digital information for processing and analysis. Thanks to speech recognition, voice control and voice search have become widely available. When compared to a person, this capability of machines is akin to hearing.
Speech recognition
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Image recognition

This is the automatic conversion of real world photos into digital information for processing and analysis. Thanks to image recognition, the identification of objects in a photo, as well as the search and grouping of images by content have become widely available. When compared to a person, this capability of machines is akin to vision.
Image recognition
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Benefits of artificial intelligence in business

AI’s potential in business is unlimited. Here it excels in customer service and process automation like data updates and billing in real time. AI also understands and predicts customer preferences well, personalizes advertising, and works around the clock in terms of support services.

Here are some concrete examples of the benefits of artificial intelligence in business.

Ads personalization

Displaying personalized ads to a customer increases their interest and loyalty, thereby improving sales. That’s why companies are working so hard to achieve this.

AI is useful here because it is able to identify patterns in the habits and actions of customers by studying their buying behaviour. Using terabytes of data analysed in the cloud, the AI then will present customised product or service offerings to customers.

Automation of client interaction

Most client interactions, such as sending emails, chatting, social networking, or phone calls, usually require human involvement. AI allows companies to automate these methods of communication, and to transfer employees to places that only a person can handle.

By learning from the data obtained from previous conversations, AI can more efficiently respond to client requests and process them automatically. AI today already provides 65% of interactions with clients, all while communicating so that it is difficult to recognize a machine on the other end.

Work automation

If a large stream of customers or employees who need help passes through your company’s systems every day, then you can shift some processes to machines. Artificial intelligence in the service of business can cope with routine work faster than people.

For instance, AI is useful for railways and airlines that serve hundreds of thousands of people (they often have problems with tickets). AI is also useful for fleets that track the geolocation of their trucks, buses, and taxis. In this area, it can report information about departure/arrival times, where the transport is now, and what route it is taking.

Business automation

AI can use related technologies to increase the percentage of automation in business. Due to the exclusion of the human factor, the number of errors is reduced to a minimum.

For instance, car factories are using AI to control a robotic system when assembling cars, and plants are using AI to maintain ideal temperatures with smart heating. In Japan, robots are already working as hotel administrators. Artificial intelligence in the hotel business automates registration and booking, as well as processes guest requests.

Predicting results

AI is able to predict results with high accuracy based on data analysis. It can see certain patterns and trends in the data, such as buyer behaviour. These findings will tell you which products will sell better, in what volumes, and in what season.

Machine predictions are useful not only in retail, but in many other areas as well. Take, for instance, trading and investment management: here AI can predict price fluctuations for stocks, commodities, currencies, and cryptocurrencies.

Areas where artificial intelligence can be applied in business

AI is everywhere: people use it on smartphones, companies also use mobile apps with artificial intelligence (but more often web apps). For some businesses this isn’t enough. They order the development of apps needed for their specific tasks. Let’s list the areas where our customers most often come from.

Banking and credit services

Banks use AI to detect fraudulent activity. They train models on a very large sample of data containing the transactions of both fraudsters and legitimate users. By identifying patterns, machines are able to determine whether a regular transaction is carried out by the real owner of the account/card or a dark person.

Credit departments are increasingly implementing AI to better and more accurately assess customer creditworthiness. According to bankers, machines already make more than half of the decisions on loan applications, reducing consideration time and issuance from several days to half an hour.


Every second online shop has a chat via which visitors contact salespeople and support. The first contact, as a rule, occurs with a smart chatbot. The AI that operates in most chatbots understands natural language, so it’s just as natural as a person to advise customers, respond to requests, and offer products or services.

Another common use is automated recommendation systems on major marketplaces like Amazon with its SageMaker. They self-learn by analysing customers’ preferences to make them individual offers, as well as take into account the demand for goods.


As cyberattacks grow and hacker techniques become more complex, there aren’t enough specialists to protect against them in advance, rather than deal with the consequences of hacks. In today’s world, not only leading IT companies, but also many other businesses have begun to increase cybersecurity spending.

Businesses need someone to detect threats and repel attacks in real time, and in the worst-case scenario, instantly fix problems caused by a hack. All of this can be provided by AI trained in cybersecurity.


AI is becoming the bedrock for building the next generation of financial services. It helps fintech companies compete with traditional credit and insurance organisations, or interact with them in B2B. And in B2C, financial planning and savings management robo-advisers have proven themselves well.
AI for FinTech
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AI helps traders and hedge funds collect, process, and analyse market data, build trading algorithms and strategies. Due to its multitasking ability and speed, it modernises trading on any market, while at the same time reducing losses and increasing profits.
AI for trading
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That’s where AI manifests itself much more actively. It engages customers by recommending products and improving the personalization of the experience. It customises ads by automating pricing and PPC campaigns. It supports websites by creating content and optimising pages.
AI for marketing
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Examples of artificial intelligence-based apps

Everyone is already accustomed to virtual assistants from IT giants in everyday life. But in business, such apps with AI are sometimes surprising, especially when they carry out narrow-profile tasks. As examples, here are a few cool apps that you can already use (or order a custom one). And there’s also an even cooler system from Tesla to compare AI capabilities.

GitHub Copilot

It’s a neural network programming assistant developed by Microsoft and OpenAI. Even if you’re not an IT company, you probably have an IT department. Your programmers could use a coding adviser like this or someone to write the code for them.

The Codex model underlying GitHub Copilot is well versed in algorithmic rules, as well as in development principles and methods. It knows the programming languages Go, JavaScript, Python, Ruby, and TypeScript. It analyses the finished or typed code and comments on it, and then advises to refine the lines and functions. As the developer either accepts or rejects advice, the model adapts to their style and becomes a smarter partner.

Legal Robot

This is a robo-lawyer developed by a company of the same name. Even if you’re not a law firm, your pair of in-house lawyers could use a vigilant assistant who won’t miss a single mistake.

Legal Robot runs machine learning on thousands of samples of legal documents. It then translates complex legalese into plain English, presenting contracts in a more understandable manner. It is also adept at identifying potential issues in legal documents, such as ambiguous definitions and risky wording.

Autopilot 3.0

The well-known electric vehicle manufacturer Tesla is actively using AI in its autonomous driving system Autopilot 3.0. The company aims to achieve complete autonomy so that an individual isn’t involved in driving.

Not long ago, Tesla publicly demonstrated how the neural network perceives the road, the movement of other vehicles and pedestrians, as well as how it analyses obstacles in its path. The entire Autopilot 3.0 system includes 48 neural networks that engineers spent 50,000 hours training.

Introducing artificial intelligence in your business

As the speed of AI advances rapidly, business people are also swiftly trying to implement and use it. This is proven by the results of a survey of US company executives about their practice of introducing artificial intelligence into business:

  • 33% have started implementing limited use cases
  • 25% have processes fully supported by AI
  • 21% have launched promising proofs of concept and are looking to scale them up
  • 14% have conducted multiple proofs of concept with limited success
  • 7% do not yet use AI, but are exploring the possibility of doing so

Those who’ve incorporated artificial intelligence into business processes are already benefiting from cost reductions and efficiency gains. The remainder lose them in competition and leave their respective markets.

If you, too, are thinking about bringing AI to your business, Polygant can develop the apps you need. To find out the cost and timing of development for specific tasks, fill out the application form. We’ll get back to you immediately and discuss all the details!

Service Testimonials

Very happy with our partnership with Polygant to bring AI to our marketplace to predict user preferences and recommend products. Their team has extensive experience with AI and a deep understanding of the client’s goals and concerns. With their help, sales on our platform grew by almost a third after only a month of implementation. Further growth exceeded our expectations 🙂

Alessandro Rossi