How to use machine learning in business? AI & Machine Learning Development & Outsourcing – iTizzi Custom Software Development Company, Kyiv, Odesa, Lviv, Ukraine

A huge amount of data is generated daily by various enterprises. According to the forecast, 463 exabytes of data will be created daily by 2025. This makes performing data analysis tasks critical in business processes for many companies in various industries.

Business revenue can be increased with machine learning by expanding data analytics capabilities to get more information, with greater quality and speed. In fact, 45% of those who have implemented machine learning in their business say that there are benefits of this technology in terms of access to more comprehensive data analysis.

Gaining this data through predicting business results, improving business strategy, and engaging more with customers is driven by different paths to revenue growth. Used strategically, these ideas are key to a business gaining a competitive advantage over its competitors in the marketplace.

It is important that companies and businesses in Ukraine are aware of the possibilities of machine learning in order to make informed and relevant decisions in the areas of proposed investments. Many companies need to consider whether their business will benefit from machine learning.

How can machine learning add value to your business?

Machine Learning is making a great contribution to various enterprises, showing steady progress in the fields of use. However, here are the specific details of how it adds value to the business:

Setting up the environment and user experience

Setting up the environment and user experience speaks volumes about how companies can benefit. This allows you to improve customer engagement with machine learning insights. Companies can better identify, understand and respond to customer needs, which can even lead to a potential increase in sales. Finding products using personalization based on the user’s search and purchase history is useful, especially in sales and marketing. Machine learning data analytics can also improve customer segmentation by predicting and separating profitable customers from risky ones in the insurance and finance industries.

Computer vision

Computer vision is constantly improving its ability to create numerical and symbolic information from images and other large data. Various companies have adopted computer vision and have benefited from what it offers. In particular, solutions in the field of biometrics, forensics, augmented reality and industrial quality control. This technology has opened up endless possibilities by activating the recognition of visual content.

Digital content processing

Machine learning plays an important role in ensuring that huge amounts of content are processed quickly. The most common use case is document search, including categorizing documents by subject and keyword, automatically summarizing content, and extracting relevant information from large volumes of content. This facilitates the search process by effectively organizing it in an organized manner.

Forecasts, estimates, sales forecasts

The business must constantly be innovative and flexible to meet the growing needs of its customers. Machine learning techniques are regularly used to predict the demand for products and services. Thanks to this, companies in different markets and in different fields of activity continuously prosper and remain relevant, no matter how fast technology and business develop. Demand forecasting allows businesses to manage their inventory, assess the economic return on promotions and reduce costs. It can also provide predictive analytics that help analyze old and current data to predict future results. It benefits the financial industry by predicting fluctuations in currency and stock prices, and even helps predict outbreaks of healthcare infections. Machine learning in healthcare is constantly growing and evolving along with the growing number of applications in use.

Anomaly detection

Anomaly detection with machine learning makes it easy to detect problems such as structural defects, errors, and even fraud. This is especially useful in detecting intrusions that can potentially damage information systems. In addition, anomaly detection can easily detect strange activities in large and complex big data sets, which can be useful in the fields of banking, security, science, medicine, and marketing.

Effects for the business of Kiev, Vinnitsa, Dnipro from the introduction of machine learning and AI

Machine learning opens up great business opportunities in Ukraine and Eastern Europe, so the results are guaranteed to improve. Here are some of the benefits of ML for your business:

Improved customer experience and functionality

Machine learning is capable of creating patterns that allow different companies to learn more about their users. Service personalization helps businesses stay attractive and relevant by knowing what songs customers are listening to on music sites or what products they can buy. The ability to provide personalized real-time customer support through these tools will lead to better customer service, resulting in continuous sales growth and customer loyalty.

Improved business strategy, processes and business logic

Machine learning models help improve business strategy by allowing you to create customized offers for customers based on the data they have. For example, dynamic price optimization for revenue management is a widely used tool in the retail, automotive, mobile, and even power industries to leverage data on consumer preferences and purchasing patterns. This helps to increase the likelihood of sales while generating higher profit margins across multiple industries.

Competitive advantages

Machine learning has consistently recommended itself as the most popular technology in rapidly growing business sectors. Machine learning makes it easier for businesses to analyze massive amounts of data, create detailed customer profiles, and gain a competitive edge in the marketplace.

The benefits of AI development and Machine Learning include:

• Improving customer understanding;
• Competitive advantage;
• More extensive data analysis;
• Improving the efficiency of the internal process;
• Faster data analysis;
• Reduction of expenses;
• Improving the efficiency of the external process.

How to bring machine learning to business?

ITizzi Software Development Company in Odessa, Lviv recommends the following strategically useful steps to develop and implement machine learning and AI for your business:

• Analysis of business processes and goals.

When incorporating machine learning into your business workflow, the first steps include understanding the goals and expectations of the project and creating initial queries. Data scientists examine the data to better develop an intuitive understanding of the problem, and then together with stakeholders draw up preliminary plans indicating the amount of work to be done.

• Collection and preparation of data

Another important step is to prepare by analyzing, visualizing and better understanding the most important data by preprocessing and transforming it to build the final dataset from the original information.

• Development of the model

This step allows you to test several models before deciding which one gives the most accurate results. By experimenting with different types of models, choosing features and adjusting parameters, it will be easier to determine which model is being refitted and which is not performing well.

• Assessing and deploying the model

Data scientists evaluate the accuracy of a model by analyzing the results from machine learning models and continually tweak their parameters until the most appropriate results are obtained. At the final stage of development, we can launch the model into production.

• Measuring the results of the introduction of machine learning.

It is important to determine how to measure the impact of the decision and determine the potential ROI of machine learning. Businesses will also have to choose between hiring data scientists, software developers, or outsourcing machine learning tasks. By choosing a personalized service, you enable your business to receive customized solutions that meet the specific requirements that you set yourself.

At iTizzi, we also provide outsourcing of machine learning tasks.

Why does your company need outsourcing for machine learning development?

In the past, machine learning (ML) was all about performance and cost. However, with advances in technology, experts predict that the use of machine learning in business operations will double compared to past years as businesses recognize that machine learning helps companies save significant cost and labor savings. Machine learning gives companies an edge when it comes to solving problems on their own, improving customer service, collecting large datasets and delivering valuable business ideas, and adjusting business operations that can give the company a competitive edge.

It was predicted that in 2018 large and medium-sized enterprises will increase the use of machine learning, and in 2020 it will double. Analysts then predicted that machine learning would have more significant growth in investment and adoption worldwide.

Here are some considerations regarding the benefits and risks of outsourcing machine learning, as well as tips to help you choose the right partner – iTizzi Software Development Company.

Risks of outsourcing machine learning

Communication deficiencies. One of the most common risks is communication pitfalls. Communication lines may be underdeveloped, especially if external staff is away from the office. However, once communication standards are established between company teams, conflicts and misunderstandings can be prevented.

Project management error. Outsourcing teams or machine learning consulting companies tend to take on many different projects for different enterprises, which can often lead to errors and delays in meeting requirements. At iTizzi, we always set a detailed schedule and agree on a reasonable time frame to avoid such conflicts. It is also very important that we regularly schedule meetings with the customer so that he is always aware of the progress of the project.

Lack of knowledge about the subject area. The good quality of models in any project largely depends on knowledge of the subject area. If you do not have sufficient knowledge in the domain, the development of functions as a key component of the implementation of machine learning runs the risk of failure. In order to avoid conflicts in the project, we hire only real specialists in their field, carefully checking their competencies, skills and knowledge in the business niche.

How to avoid the risks of ML outsourcing?

Choose the right and professional provider – iTizzi Software Development Company. The key to understanding whether the company you choose to provide your services is having sufficient experience in implementing data projects.

Sign the agreement. It is important to have legal documents that clearly spell out the terms and conditions and agreements between your company and your outsourcing partner.

Explain the main goals and ideas of the project. To ensure the success of your company’s collaboration with your chosen external team, it’s important that you both are on the same page when it comes to ideas and business goals. Constant communication is key and it is best to have a regular meeting schedule and an open line in case you need clarification during a project.

Be aware of the project. Management tools are critical to the success of your project. It also plays an important role in conflict prevention. Using project management tools, you can assign tasks, provide details, set deadlines, track progress, and schedule meetings with the company.

Benefits of Machine Learning Development and Outsourcing at iTizzi Software Development Company, Eastern Europe

High-level data scientists. Implementing machine learning solutions requires extensive knowledge and sophisticated development experience. Hence, it is necessary to have high-level specialists to work on machine learning projects. Having in-house developers can be costly, however, while partnering with an ITizzi IT service provider that meets your requirements is cost-effective and easier.

Time-saving and cost-effective development. Neural networks perform many complex tasks such as categorizing information, making decisions, and the ability to make predictions for the future based on data. This can be quite difficult and time-consuming. Hence, it is beneficial to have an outsourced development team that can speed up the neural network development process. Engaging external iTizzi partners allows you to build teams faster and scale them as needed. Also important is the fact that experienced outsourcing company iTizzi has the exemplary hardware and software required to develop machine learning, which will save you on additional costs.

The best resources for delivering machine learning services. When it comes to building predictive algorithms for decision-making, it is important to have teams working hard on it. Team members may lack tools to analyze data, especially when handling machine learning errors. Outsourcing teams are considered very useful as they have access to a wide range of libraries and tools to collect, explore, prepare, and visualize datasets.

Effective data management and security. Outsourcing developers for machine learning projects is useful when it comes to protecting sensitive information regarding your company’s data. In addition, experienced professionals at iTizzi will take good care of implementing proper and systematic management, organization and storage of data across different platforms.

Summary

Machine learning development in Kyiv, Dnipro, is one of the brightest and most effective approaches to business processes. This is why companies choose to integrate machine learning and artificial intelligence technologies into their businesses. However, companies may have trouble finding and managing machine learning developers and AI specialists, as it is more expensive and time-consuming.

Therefore, iTizzi offers a comprehensive outsourcing service for machine learning consulting, which is a more cost-effective choice, while providing a higher quality of work compared to hiring a number of specialists yourself.

With that said, outsourcing machine learning is a smarter choice for machine learning, given that outsourcing teams have more tools, more talent, and professionals with more experience and expertise in machine learning development.

The iTizzi Software Development Company team of software developers and data scientists will guide you through the entire process of developing machine learning for business. We will take a close look at the specifics of your business, discuss all your requirements and business goals, explain the wide range of machine learning opportunities and explain which methods are right for you.

We handle data-driven processes from data collection and preprocessing to preparing datasets for efficient modeling. Then, our experts create the optimal machine learning model, evaluating its accuracy, to provide unique machine learning solutions.