AI-Powered Visualization for Improving the Ecommerce Customer Experience

As ecommerce continues to evolve, customer expectations are higher than ever. Shoppers no longer settle for static product images or vague descriptions — they want to interact with products, visualize them in their spaces, and make informed decisions with confidence. AI-powered visualization technology is transforming the ecommerce landscape, enabling businesses to deliver immersive and personalized experiences that drive customer satisfaction and boost sales.

The Role of AI-Powered Visualization in Ecommerce

AI-powered visualization uses advanced algorithms and machine learning to create realistic, interactive representations of products. This technology allows customers to see products in 3D, customize features in real time, and even visualize items in their own environments through augmented reality (AR).

For ecommerce businesses, this innovation not only enhances the shopping experience but also reduces uncertainties that often lead to cart abandonment. By providing a clearer understanding of how products will look and fit, companies can foster greater consumer trust and reduce return rates.

How AI Visualization Enhances the Customer Journey

Interactive Product Previews

Static images can only show so much. AI-powered visualization tools provide 360-degree views, enabling customers to rotate and inspect products from every angle. This interactive experience is particularly useful for industries like home improvement, fashion, and furniture, where visual appeal and fit are crucial.

For example, Wizart Visualizer offers cutting-edge AI-powered visualization that allows customers to see how flooring, wallpaper, or other home improvement materials will look in their spaces. Users can upload a photo of their room and instantly preview various design options, empowering them to make more confident purchase decisions. (Read more on this topic: Solutions for selling finishing materials online)

Personalized Shopping Experiences

AI-driven visualization tools analyze customer preferences and behavior to deliver tailored recommendations. This personalization helps shoppers find products that align with their style and needs. With the ability to customize color, size, and design in real time, customers are more likely to engage with products and complete purchases.

For instance, a customer shopping for flooring can use AI-powered visualization tools to explore different materials, compare textures, and visualize how each option complements their room. This level of personalization not only enhances customer satisfaction but also increases the likelihood of conversion.

Augmented Reality (AR) Integration

AR technology powered by AI is redefining the online shopping experience. Customers can virtually place products in their environment using their smartphones, helping them understand the scale and aesthetics before making a purchase. This feature is especially valuable for home décor and furniture brands.

By integrating AI-powered visualization solutions, ecommerce platforms can bridge the gap between physical and digital shopping experiences. Customers no longer need to rely solely on imagination — they can see exactly how a new rug, paint color, or wallpaper will look in their space, reducing hesitation and increasing purchasing confidence.

Reducing Returns and Increasing Satisfaction

One of the biggest challenges in ecommerce is handling product returns. Misaligned customer expectations often lead to dissatisfaction and increased return rates. AI-powered visualization mitigates this risk by providing highly accurate and detailed product representations.

When customers can see an accurate preview of how a product fits their space or lifestyle, they are less likely to encounter unpleasant surprises. Visualization tools ensure that what customers see online closely matches the reality, leading to higher satisfaction and lower return rates.

The Future of AI-Powered Visualization in Ecommerce

As technology advances, AI-powered visualization will become even more immersive and intuitive. Innovations like virtual showrooms and AI-generated design recommendations will further enhance the shopping journey, making online experiences as engaging as physical ones.

For businesses, adopting AI visualization is no longer optional — it is essential to meet customer expectations and drive growth. With solutions like Wizart Visualizer, companies can offer interactive, personalized experiences that set them apart from competitors, foster customer loyalty, and increase conversions.

In conclusion, AI-powered visualization is revolutionizing ecommerce by providing customers with more confidence, reducing uncertainties, and improving overall satisfaction. Embracing this technology today ensures businesses are well-positioned for the future of digital commerce.

In the fast-paced world of business and technology, custom software development has become a critical component for companies seeking to address specific needs and enhance their operations. Whether in the B2B or B2C sector, creating tailored software solutions requires careful consideration of unique challenges and requirements.

B2B and B2C Software Definitions

Before discussing the specifics, let’s briefly define B2B and B2C software.

B2B software refers to applications and platforms designed to cater to the needs of businesses, for example, targeting professionals such as accountants, lawyers, and other specialized roles. These applications often have complex functionalities tailored to specific business processes and require a deep understanding of the industry.

On the other hand, B2C software serves the general public and focuses on individual consumers. B2C applications are typically designed to be user-friendly, intuitive, and visually appealing, as they cater to a broader audience with varying levels of technical expertise.

In custom software development, B2B and B2C projects diverge significantly, demanding tailored approaches to address each sector’s unique challenges. As we explored the intricacies of both domains, we identified five key differences that stand out in the development process:

1. Differences in Testing Hypotheses.
2. Update frequency.
3. Varied system loads.
4. Diverse monetization models.
5. The start of users’ interaction with the software.

Let’s delve deeper into these five distinctions to understand better how the specificities of the B2B and B2C sectors impact the development process.

Differences in Testing Hypotheses

One key difference between B2B and B2C software development lies in the testing of hypotheses. In B2B, it is more challenging to test quantitative hypotheses due to a smaller target audience: each business has its unique workflow and requirements. B2B applications often serve niche industries or specialized functions, which limits the number of potential users available for testing.

Additionally, B2B software solutions may require extensive integration with existing systems and processes within the organization, making it more difficult to isolate and test specific hypotheses in a controlled environment. As a result, the development team must adopt a more personalized and iterative approach to gather feedback and validate assumptions effectively.

Update Frequency

B2C software products typically demand more frequent updates to stay competitive and retain users. Consumers expect constant improvements, new features, and bug fixes to enhance their experience continuously. Rapid development cycles and quick releases are critical in the B2C sector to address user feedback promptly and stay ahead of the competition.

However, frequent updates in the B2B landscape may disrupt users’ workflow and reduce productivity. Communicating effectively with organizations, involving them in the update planning process, and ensuring that updates can be seamlessly integrated into their existing workflows is essential.

Varied System Loads

B2C platforms typically experience higher user loads compared to B2B systems. The sheer number of users accessing B2C applications simultaneously can create significant server loads and demand a robust infrastructure to maintain smooth functionality. High scalability and performance are essential in B2C software development to ensure the application can handle the expected user load without compromising user experience.

On the other hand, in the B2B landscape, the focus is often on optimizing the system to handle complex computations and data processing. B2B platforms may have a smaller user base, but the calculations and data analysis required can be more intricate and resource-intensive. This involves careful planning and design to ensure the system can efficiently handle the workload while maintaining accuracy and reliability.

Diverse Monetization Models

B2B apps often offer subscription-based services to organizations, providing access to specialized tools and features. The subscription model allows B2B software providers to offer different tiers of service and pricing options based on each client’s specific needs. Additionally, B2B applications may require integrating payment systems and gateways to facilitate smooth subscription management and invoicing processes.

In contrast, B2C applications are often free for users but generate revenue through advertising, in-app purchases, or premium subscriptions. B2C software development involves incorporating ad-serving platforms, in-app purchase systems, and user profile management to facilitate revenue generation. The focus is on offering opportunities for users to make additional purchases or engage with sponsored content.

The Start of Users’ Interaction with the Software

Implementing a new software solution in the B2B sector often requires user training as the systems are tailored to specific business processes and may not be as intuitive for employees. Unlike B2C applications designed with user-friendliness in mind, B2B platforms often serve complex business needs, necessitating thorough onboarding and training to maximize their benefits.

The training process may involve:

• Providing instructional materials.
• Conducting workshops or webinars.
• Offering ongoing support to help users navigate the intricacies of the software.

Considering the time and resources required to train employees effectively is crucial, as it can directly impact user adoption, productivity, and the overall success of the B2B software solution.

Exposit’s Expertise in B2B and B2C Projects

Custom software development in the B2B and B2C sectors presents unique challenges, requiring tailored approaches to meet diverse business and consumer needs. At Exposit, we have extensive experience in both realms.

Our portfolio reflects a wide array of projects, illustrating our expertise in tackling complex B2B projects, optimizing workflows, and empowering organizations with cutting-edge technology. Simultaneously, we have excelled in creating user-centric B2C applications, captivating audiences through intuitive interfaces and innovative features.

Whether you need custom B2B software to improve your business processes or engaging B2C applications to attract consumers, Exposit is here to help. Our seasoned team is poised to embark on your next software journey, ensuring a smooth development process that satisfies your goals and sets new industry standards.

With the advancements in artificial intelligence, there has been a growing interest in exploring the capabilities of AI models like the ChatGPT application. While ChatGPT, a language model developed by OpenAI, has shown impressive abilities in generating text and answering questions, there are several reasons why it cannot fully replace programmers in software development. In this article, we will discuss four key reasons suggested by our ML specialists why developers remain essential in the field:

“The ChatGPT (v. 3.5) knowledge base is limited to September 2021, while the developer has access to more recent information and experience in a specific field. Versions of libraries, frameworks, or programming languages often get updated, and ChatGPT may generate code with deprecated functions.

ChatGPT operates based on a sequence of questions and answers; it cannot see the bigger picture or have a broad context. The developer can consider architectural decisions, performance optimization, unique project requirements, and other factors that cannot be fully replicated in the model.

Software development requires creativity and intuition. Developers can propose new ideas, find innovative problem-solving approaches, and apply their professional experience within the development context. ChatGPT lacks this intuition and is limited in generating new ideas.

Ethical considerations are crucial in software development, and decisions must align with legal requirements while prioritizing data security and confidentiality. However, ChatGPT cannot consider these factors.”

Ekaterina Kosareva, ML Engineer

Limited Knowledge Base

One of the limitations of the ChatGPT application is its knowledge base, which is constrained by its training data. ChatGPT’s training only extends until September 2021, while developers have access to more up-to-date information and hands-on experience in specific domains. Libraries, frameworks, and programming languages undergo frequent updates, and ChatGPT may generate code with outdated functionalities or practices. The ever-evolving nature of programming necessitates developers’ continuous learning and adaptation, which cannot be fully replicated by an AI model trained on fixed data.

Furthermore, programmers possess domain expertise that goes beyond mere knowledge. They understand the intricacies of various programming languages, frameworks, and tools, enabling them to make informed decisions based on current industry trends and best practices. This contextual understanding allows specialists to deliver robust and efficient solutions, tailored to the specific needs of the project.

Lack of Full Context

ChatGPT operates on a question-and-answer framework, which limits its ability to perceive the bigger picture or have a broad context. While it can provide answers and guidance based on individual questions, it cannot fully grasp the overall architectural decisions, performance optimization, and unique project requirements. Programmers, on the other hand, possess the capacity to evaluate trade-offs, make informed decisions, and design software solutions with a comprehensive understanding of the project’s scope.

Programmers take into account factors such as scalability, maintainability, and extensibility when designing software systems. They consider the interactions between different components, identify potential bottlenecks, and optimize performance. By having a holistic view of the project, programmers can create software that meets both functional and non-functional requirements, ensuring that the final product is efficient, robust, and reliable.

Inability to Make Creative and Intuitive Decisions

Software development often requires creativity and intuition. While ChatGPT coding for developers can provide general guidance, it lacks the intuition and creativity that humans bring to the table. Programmers contribute fresh ideas, find innovative problem-solving approaches, and apply their professional expertise to development contexts.

Software engineers are not just code generators; they are problem solvers. They can identify alternative solutions, consider different design patterns, and adapt their approaches based on the project’s unique needs. Their experience and creativity enable them to think outside the box, propose new ideas, and address complex challenges that may arise during development. This ability to think critically and creatively is crucial for developing innovative software solutions that push the boundaries of technology.

Inability to Consider Ethical Issues and Current Legislation

Developing software entails considering ethical considerations and adhering to legal frameworks, ensuring data security, and privacy. Programmers are responsible for making ethical decisions and ensuring that software complies with relevant laws and regulations. They possess the necessary knowledge and expertise to navigate the complexities of ethics and legal requirements, safeguard user interests, and create responsible software solutions.

ChatGPT, however, lacks the capability to incorporate these critical factors into its decision-making process. Ethical considerations, such as data privacy and algorithmic bias, require human judgment and moral reasoning. Developers are equipped with the ethical framework to assess potential risks, make informed choices, and prioritize user safety and privacy. By involving programmers in the development process, businesses can mitigate ethical and legal challenges, ensuring that the software solutions they create align with ethical guidelines and legal requirements.

“ChatGPT and other large language models (LLMs) can currently only solve common tasks. Furthermore, it is still the responsibility of the programmer to implement the code generated by neural networks. Yes, this technology can already significantly simplify developers’ lives, but it has limitations. For example, how would one use a neural network to write a large-scale service? And how would one modify it to support changes?

In theory, the level of abstraction will increase in the future, and developers will collectively start writing technical specifications (TS) for neural networks. However, at present, this seems more labor-intensive than contemporary programming practices. Today, creating precise TS for LLMs requires an immense amount of effort, comparable to or even exceeding the effort needed to write the desired code by specialists.

This becomes especially challenging when it comes to software updates. Making changes to code already generated by a neural network requires clear instructions, which can be difficult to formulate and may become grueling.

The responsibility for the performance of solutions generated by neural networks should also be considered. Ultimately, the developer remains accountable. What are the consequences for ChatGPT if it provides an incorrect answer? None. However, for the developer, it is a different story. As many examples demonstrate, ChatGPT cannot recognize errors and often confidently presents false solutions as correct.

A developer’s work involves an indescribable, unformalizable aspect, which may follow specific ideas or internal motivations. We are all familiar with the example of an “Italian strike” where workers start working like robots, strictly following regulations, and work grinds to a halt. It is unlikely that we will soon see systems capable of mimicking these complex constructs. It would require something more sophisticated than large language models.”

Evgenii Pustozerov, ML Engineer

The synergy between programmers and AI models holds great potential for advancing software development. By combining the strengths of both, we can harness the power of AI while benefiting from the creativity, context awareness, ethical considerations, and problem-solving abilities that human programmers bring to the table. The collaboration between ChatGPT and developers will continue to shape the future of software development, enabling us to create innovative, responsible, and efficient software solutions that meet the evolving needs of businesses.

At Exposit, we understand the importance of this collaboration and have a team of experts who possess profound domain and tech knowledge and experience in developing cutting-edge solutions. Also, we have experts in artificial intelligence, for example, Computer Vision, specializing in leveraging AI technologies to enhance software capabilities. Contact us today to discuss your business needs and explore the possibilities of integrating AI technologies into your projects.

4 Reasons Why ChatGPT Cannot Replace Programmers was originally published in Predict on Medium, where people are continuing the conversation by highlighting and responding to this story.

Credit score software has become essential to the lending industry in recent years. It allows financial institutions to assess the creditworthiness of potential borrowers quickly and accurately, enabling them to make informed decisions on loan approvals and interest rates.

Credit risk decisioning is based on analyzing objective data: an individual’s credit history, payment behavior, and other factors. That way, credit scoring solutions have enabled financial companies to reduce loan defaults and improve profitability. As these platforms evolve and advance, they undoubtedly play a vital role in shaping the industry’s future.

Choose Between Traditional and Alternative Credit Scoring

While traditional credit scoring methods have proven effective, alternative credit scoring has emerged in recent years that offer additional benefits.

Traditional scoring typically relies on limited data points to determine creditworthiness, such as credit history and payment behavior. However, alternative credit score platforms incorporate a broader range of data sources, for example, utility bill payments, employment, or rental history. This additional information allows lenders to gain a more comprehensive understanding of an individual’s financial situation.

Alternative scoring also offers greater flexibility for people with limited credit histories or non-traditional sources of income. Furthermore, it can also reduce bias in the credit decision-making process. Traditional credit scoring methods may inadvertently discriminate against certain groups, for example, low-income individuals. Alternative credit scoring models can help eliminate these biases by using more diverse data points in their assessments.

Consider Using Open Banking for Alternative Scoring

One of the primary sources of data for alternative credit scoring is transactional data, which is made possible through Open Banking. This includes income and expenditure patterns, cash flow, and debt-to-income ratio, which can provide a more comprehensive understanding of an individual’s financial health.

In addition to transactional data, alternative credit scoring models may also use data from non-traditional sources, such as social media activity and online shopping behavior. By analyzing this data, alternative credit scoring models can gain insights into an individual’s lifestyle and spending habits, which can be used to evaluate credit risk.

Determine Credit Scoring Criteria

Before embarking on a project to implement a new credit scoring system in your financial business, it’s essential to have a clear understanding of the criteria used to determine creditworthiness. This includes various factors, such as credit history, income, age, employment history, etc.

By clearly understanding the criteria used to determine creditworthiness, you can ensure that your credit scoring system is designed to accurately assess risk, make well-informed lending decisions, and provide a better customer experience.

Find the Reliable IT Vendor for Credit Scoring Development

When developing credit-scoring software solutions, choosing the right IT vendor that can deliver the required expertise and experience is crucial to ensure the project’s success. At Exposit, we have extensive experience in fintech solutions development.

One of our successful projects is Plend, a consumer lending marketplace that offers affordable loans based on a unique scoring system. We helped Plend to develop a fintech solution for making fairer credit deals with a better understanding of a borrower’s financial situation. The new credit analysis system includes scoring, configuration, and authentication modules in a visual dashboard.

The configuration module includes three stages within the validation process with set rules for managing loan applications. The scoring module receives the financial information about borrowers from third-party services and exchanges this data with the configuration module and its rules. At the end of the process, the lender is provided with the necessary information for deciding the result of a loan application.

Another project in the financial industry is Bankish, a credit scoring and deposit system designed for convenient interaction between financial institutions and their clients. This core banking software solution allows institutions to add and customize financial products, give credits with risk-based pricing and deposits, manage arrears, initiate outbound payments and get incoming, and communicate with customers.

We provided Bankish with a scoring module in the system to address the specific needs of each institution. The system collects a borrower’s personal data from a profile and other resources, such as age, salary level, loan and arrears history, and cost information. Based on this data using credit scoring models, it help to decide on loan issuing or rejection. However, every institution has its own custom criteria for decision-making, which was the challenge we helped our client solve.

Get Started on the Development Process

The development and implementation of a credit application software solution can significantly impact your financial company’s success. By leveraging the latest technology and data sources, you can make more informed lending decisions and offer more personalized loan terms to your customers.

At Exposit, we have vast experience developing custom credit scoring systems tailored to our client’s unique needs. Our team of experts can work with you to identify your requirements, design and develop a custom solution, and provide ongoing support and maintenance to ensure the continued success of your credit rating software.

If you want to learn more about how we can help you implement a new credit scoring system in your financial business, we invite you to schedule a consultation with our experts. Contact us today to get started.

Finding the right IT vendor who delves into the company’s specifics and challenges and offers a workable solution to address them is a non-trivial task. Sometimes, when a business turns to a software development company with a problem, they suppose the particular solution that could solve it. Unfortunately, some IT companies could name costs immediately without analyzing clients’ needs and do not offer the best way to cover them.

Another common difficulty while trying to hire an IT outsourcing company to start a project is the lack of clarity about the actual scope of work required to bring the idea to life, as well as how relevant the implemented solution or idea would be and the time and cost involved in the process. Only a team of technical specialists can answer these questions, and that’s where Presales come into play.

“What is the Presales process in the IT industry?” you may ask. At Exposit, we have developed our own Presales process, which involves working closely with clients to identify their needs and gather relevant information about their business challenges and goals. This helps us to create a tailored proposal that outlines the best possible solution and approach for the project, including timelines, budgets, and deliverables.

Here are Exposit’s Presales process steps and what clients can expect at each stage.

Collecting Primary Data

At Exposit, our Presales process’s initial stage is collecting primary data. Our managers gather all the essential information needed to clarify the client’s business challenges and identify how our services can help solve them. We present and evaluate various sample solutions to ensure they meet the client’s needs. We move on to the next stage if the client approves our ballpark solution and budget estimate.

Performing Tech Qualification

Our managers, the Head of the Competency Center (Computer Vision, Extended Reality, or others), and the Solution Architect evaluate the technical expertise required for the project and check if the company has the technical and domain expertise. If any expertise needs to be added, its criticality is determined by the manager. Also, here we clarify the availability of specialists and check with recruiting if necessary. At this stage, the client can be confident that we have the team and knowledge to complete their project successfully.

Setting Up Presale Team

This process involves forming a team to evaluate a request for proposal (RFP). The Presales Manager and Heads of Competencies identify the team members and create a collaborative workspace for them. The team is provided with all necessary information and documents, and their roles and responsibilities are defined. Ultimately, the client receives a competent and organized team to evaluate their RFP.

Analyzing Requirements

Our Business Analyst is assigned to the request at this stage and explores client input information to prepare a Work Breakdown Structure (WBS). If insufficient information exists, the specialists identify the necessary information and communicate with the client to gather them. Then, Business Analyst provides WBS to the Presales team for feedback.

In some cases, there may be an overwhelming amount of work required to identify all the requirements, and in that case, we recommend a Discovery phase to the client. The Discovery phase involves more in-depth research and analysis to understand the client’s needs and requirements fully.

Defining Architectural Approach

Our Solution Architect analyzes the client’s documentation and existing IT infrastructure to develop a solution architecture and select a technology stack. The output of this stage includes a document describing the solution architecture, a list of proprietary solutions and their costs, a technology stack, and confirmed or disproved non-functional requirements. The client receives a clear understanding of the proposed solution’s architecture, risks and assumptions, and the CI/CD delivery model.

Estimating and Planning

During the Estimating and Planning stage of the Presales process, the team gathers and analyzes the project requirements, defines roles and timelines, and creates a detailed project plan. The client benefits from a clear understanding of the project scope, cost, timeline, risks, and a comprehensive plan for its implementation. The team also addresses any questions or concerns the client may have, ensuring a smooth and transparent project estimation process.

Creating Proposal

The Presale team creates a proposal for the client using a template that includes content and a breakdown of the work to be done. The team discusses the proposal structure and fills in the necessary information, including project costs, timelines, team composition, and engagement model details. The client receives a comprehensive proposal with a summary of the solution, business goals, roadmap, technical details, team, budget, risks, additional information, and contacts for further communication.

Approving Proposal

During the “Approving Proposal” stage of the Presales process, the Presale manager requests feedback from the approval committee and makes changes if necessary. Once all interested parties agree, the client receives a finalized and approved commercial proposal. The Approval Committee reviews the proposal from various angles, including engineering, finance and legal, delivery, and resource management, to ensure its feasibility and practicality.

Presenting Proposal

At that stage, our managers present the solution to the client and answer any client’s questions. The client receives a detailed presentation of the solution, including the involvement of various team members in defending their proposal, and can make an informed decision about whether to move forward with the solution.

Receiving Client Feedback

During this stage of the Presales process, we work with the client to address any concerns or objections they may have. Our managers communicate with the client and form a plan to move forward. Our ultimate goal is to ensure the client is satisfied and ready for a productive partnership.

Signing the Contract

Our client receives a signed contract outlining the terms and conditions of the agreement between them and the company. The contract provides a clear understanding of the scope of work, deliverables, timelines, and responsibilities of both parties, so the client can be confident that the project will be executed according to the agreed-upon terms and that any potential issues will be addressed in a timely and professional manner.

Creating the Report with Analysis

The last stage of the Presales process enables us to analyze our mistakes and improve our services. The Presale manager plans and conducts a retrospective, creates a report with the results, and adds it to the company’s library. This stage helps us identify areas for improvement and ultimately enhance our offerings to serve our clients better.

“We believe that an IT service company should take the place of a “head” and be not just “hands,” a contractor, but a partner who takes responsibility for choosing and offering the best possible solutions to achieve the client’s actual business goals and solve their challenges.”

Nikita Volkunovich, Head of Presales

Presales is an essential process that can help businesses to find the right IT partner and achieve their goals effectively. It involves collaboration between the client and the IT vendor, and a good Presales team can help to identify the client’s specific business goals and requirements and provide tailored solutions that meet their needs. If you’re looking for a reliable IT vendor to help you achieve your business goals, don’t hesitate to contact Exposit and book a consultation with our team. Let us help you find the right IT partner for your business!

In recent years, microfrontends have become a popular approach for developing web applications. This methodology involves dividing a larger application into smaller, more modular components, allowing for independent development, deployment, and scaling. The approach can result in faster development times, better scalability, and more maintainable code.

In this article, we will discuss our experience working with microfrontends on a project for a media management client. Specifically, we will talk about how we used the single-spa library to divide the platform into smaller, independent components and the benefits this approach brought to the project.

Our team was engaged in improving a platform designed for the collaborative creation, management, and distribution of digital news. The client, a media management company, needed a more efficient way to develop and deploy new features for their platform. We integrated the software application with the single-spa library to address this challenge and divided the system into microfrontends.

By adopting a microfrontend approach, we were able to simplify development and deliver new features to the client faster than before. We also saw improvements in scalability, maintainability, and code reusability. Here is our experience working with microfrontends, the challenges we faced, and the benefits we gained.

When the client came to us, the initial state of the platform was as follows:

• Angular 11;
• Application (further Main-app) with over 29 modules inside, which uses more than 20 private libraries;
• Ivy is disabled because some of the 1st and 3rd party libraries are incompatible with it;
• Angular Router has only one route and custom handler (internally called Workspace Engine) for dynamic navigation. Page layout is retrieved from a server on runtime, and the URL always stays the same.
• No state management framework — all caches with calculated data, etc., were stored in multiple RxJS Subjects in Angular services;
• A lot of services are provided in the root injector and used in almost all modules. Those services are subscribed to shared stateful observables, resulting in everything being tightly coupled;
• Almost all internal libraries are in separate monorepos handled by yarn workspaces;
• There are tight budgets, as much of it another team has already spent on early microfrontends investigation.

Accordingly, the goals of our participation in the project were:

• Split one large angular application into separate micro-apps and build a microfrontend architecture using a single-spa framework with their dedicated repositories and CI/CD pipelines;
• Provide the ability to change applications’ locations on the fly without changing code.

We have identified the steps to achieve these goals:

1. Investigate single-spa, single-spa-angular, import maps, and SystemJS;
2. Split components (modules) into micro-apps gradually without breaking the whole application;
3. Ensure smooth transition of a module to micro-app without blocking other teams responsible for it;
4. Try to make it as framework-agnostic as possible.

Investigating and Solving the Initial Hurdles

single-spa and single-spa-angular

In order to use single-spa with Angular micro-apps, we needed a single-spa-angular library that is part of a single-spa official ecosystem.

As with most of the open-source libraries, we faced issues of poor and irregular support of these libraries. Single-spa-angular supported Angular 12 when Google released Angular 13, and it still fits our needs as Angular 11 was widely used in our projects. Going a bit forward, the situation hadn’t changed when Angular 14 was released and could have blocked our further updates to the next Angular versions when the time would come. Things changed when one Angular expert, the member of Open Source community, added support up to the latest Angular 15.

Unintended Use of single-spa

single-spa is positioned as a router for microfrontends. It’s recommended to register a micro-app as an application, and the application should be tied to the URL route. This concept does not fit our needs as we have only one route but multiple applications. We had to keep going with single-spa. Fortunately, it has a more advanced concept called parcels. It lets developers manually mount and unmount the application, so they are not dependent on the router anymore but responsible for its lifecycles.

Import Maps

Import Maps is a WCAG proposal to control the URLs from which the browser would fetch a dependency from ES module import. This mechanism allowed us to accomplish our goal of dynamically changing applications’ locations. It can be rewritten and redeployed on the fly with the help of a CI/CD environment.

When we started our work, the Import Maps proposal was not supported by the browsers, so we had to use either es-module-shims or SystemJS. The single-spa team highly recommended it because they were also maintaining this module loader. At the time of writing, it is still not adopted by all browsers except Chrome.

Module Federation

We were also considering using webpack Module Federation, which suited better to our case, and we could not avoid comparing it to SystemJS during development.

SystemJS was built way before the ES Modules were introduced and it is one of the options to bring modules to legacy browsers such as Internet Explorer. That means we needed to build dynamically loaded modules in a SystemJS module format, which brought such drawbacks as large module size and performance drop and could become a bottleneck in further development. Webpack didn’t have this problem, so we could use the preferred module type without any hurdles.

Module Federation is a webpack plugin for microfrontend implementation that enables us to build modules separately and form a single application on runtime. Though Module Federation seems to be just a build-time solution, forcing to define other modules and their URLs in webpack config. It can work without these definitions and load modules via URLs known only on runtime, just like the Import Maps.

Conceptually, it fitted better to our initiative than single-spa. Nonetheless, there were multiple reasons we started to use single-spa though keeping in mind possible migration to Module Federation. The reasons were:

• The business spent a year on a single-spa investigation with another team for angular microfrontend app development. They aimed to start splitting the application, and they didn’t want to spend any more resources on another discovery phase;
• Angular 11 was still using webpack 4, while Module Federation was released in webpack 5;
• In order to work with webpack 5 natively, we needed to update to Angular 12, which forces to use the Ivy rendering engine in applications. We still had many libraries and app parts that were incompatible with it, which could bring a lot of unpredictable regressions throughout the application.

We were able to test webpack 5 because, as we used yarn, we forced Angular to use it by “resolutions” config. But in the end, we faced some troubles with single-spa-angular itself and HMR, which slowed down development for some teams and their modules, so we had to revert it.

Multiple Instances of a Single App

In our project, users can open multiple instances of the same component in the same workspace. There was no problem with the requirement before microfrontend migration when dynamic workspace components became micro-apps. So, single-spa-angular did not support multiple instances of one micro-app on the same page, and when we tried to add a new instance of an app via single-spa parcels to the page, it would replace the existing one in the DOM.

We have created an adapter component for Workspace Engine that continued to work with components, but under the hood, the adapter dealt with mounting and unmounting the micro-apps. It also allowed to utilize engine’s ability to create container elements when needed, thus making it empty, and nothing is overwritten on the new instance mount. That’s because it rewrites everything inside the container element.

Debug

DevTools Failures

Debugging is an essential process for developers, including instruments for identifying bugs and their sources. Imagine DevTools started to crash every time you opened them, making debugging nearly impossible. That’s what happened to our micro-apps when Chrome 102 was publicly released. Another Chrome update stopped downloading Source Maps. We couldn’t identify the reason for such behavior, but everything surprisingly got fixed with Chrome 106 DevTools.

Source Map Namespaces

Naturally, different applications might have files with the same name. While it is not a problem in a single application, we faced a Source Map name clashing issue as we split several applications and utility modules. Webpack and Angular CLI use the default Source Map namespace if you do not set it explicitly in the configuration.

So, when a developer has different Source Maps with the same file path, they will see only one Source Map from one module in DevTools at runtime, and it becomes difficult to debug other modules as it makes them debug minified bundle. To improve the developer experience, we recommend configuring the namespace in webpack’s SourceMapDevTool plugin in every application and utility module. As a result, it becomes able to see each module source as a separate folder tree in DevTools.

Open-source and Documentation

Documentation is undoubtedly important, but it is time-consuming to cover and keep every topic up-to-date, so some docs miss nuances and little details. That’s the case for single-spa and SystemJS. We found most of the answers in its source code rather than documentation. We strongly recommend reviewing and understanding library sources used to check concerns and hypotheses when documentation does not help.

From Hurdles to Progress: Navigating the Main Work Process, Bug Fixes, and Improvements

Root Application

From the very start of the project, we tried to be as close as possible to the single-spa recommended architecture and setup . However, we couldn’t follow them most of the time due to limited time and the tight coupling of application modules.

Root application, or as single-spa docs call it, root config, is a framework agnostic entry point to our microfrontend world that:

• bootstraps single-spa;
• downloads import map and bootstraps SystemJS with it;
• orchestrates the applications.

While the first points fit our goals, the latter was a problem as our application (the Main-app) had its own orchestrator — the Workspace Engine. Needless to say that it was a foundation for the whole application, and it was tightly coupled to Angular component lifecycles itself. Rewriting this functionality would have taken lots of effort and could have introduced many breaking changes. So the orchestration flow we ended up with was to register and bootstrap Main-app and delegate further routing concerns to it by making it able to mount and unmount micro-apps and not components as it was before.

Later, the root app got some new responsibilities as an entry point:

• bootstrap utility modules;
• share common styles.

Micro-apps Splitting

We developed a plan for micro-apps splitting:

1. Identify core module that should be migrated as micro-app and its feature modules.
2. Extract feature modules from the Main-app to libraries.
3. Migrate core module as micro-app.
4. Use extracted module like a lib in micro-app.
5. Replace the usage of core module in Main-app with the micro-app.

All of the steps would have worked if the core module doesn’t depend on other parts of the Main-app, but in most cases, it depends. Splitting to micro-apps was forced, so we had no time to move or refactor multiple places in the app to make them less coupled.

Under these conditions, we chose a way with shared angular services between micro-apps.

Angular Shared Services Mechanism

The Angular shared services mechanism is a similar mechanism (like for libraries) with the forRoot() method of the module. We created an instance of service in Main-app and registered it in the shared utility library. Then micro-app got it from shared lib, and via angular providers replaced the instance for lib module injector. This mechanism brings several drawbacks but allows to start micro-apps splitting faster.

We have identified several problems with shared services:

• tight cross micro-apps coupling;
• boilerplate in application modules;
• libs versions mismatch, which brings injection and runtime errors;
• version hell;
• duplication of libs in apps which brings large bundles;
• sources duplication in devtool and confusing debug flows.

In any case, we strived to reduce the number of such services.

According to each shared service usage and logic inside, we needed to apply the following approaches to refactoring in order of possibility and less time-consuming:

1. If possible, make a service standalone, refactor to allow micro-apps to use it separately, and be aware not to multiply network calls to the backend in a case with multiple service instances.
2. Refactor direct calls of service to events-driven subsystem using event-utility-lib.
3. Extract shared state or full logic to shared utility library related to micro-app or separated app parts.

For example, services of profile-micro-app can be refactored with profile-utility-lib usage, and some workspace engine services can be refactored to workspace util lib., etc.

As a result, all shared angular services should be removed from our single-spa environment, and all connections between micro-apps should be framework agnostic, which means we can have service instances. Still, they should be only regular Javascript Objects without angular metadata.

Shared Utility Modules

We realized we couldn’t follow the concept of a standalone micro-app from the original microfrontends idea, and we needed to store these shared services somewhere, share configs, cache, and state between micro-apps.

The single-spa documentation here helped us with utility modules. In general, there are small pieces of logic (a couple of functions, a few native js services) that are provided at runtime from Root-app to other micro-apps via webpack externals.

As a result, we created a few utility libs to share, which purposes were:

• mount/unmount parcels, store parcels cache, manage the lifecycle of micro-apps;
• store shared services, provide a special Angular decorator to check — is there more than one service instance exists;
• store angular NgZone to keep change detection works between micro-apps;
• store common backend clients to share cache and avoid unnecessary backend calls;
• provide an events API between micro-app to reduce shared services usage;
• keep micro-app-specific logic and provide micro-app open API for other apps.

Integration and Usage of Micro-apps

After we extracted the module and created a micro-app, we could add it to the Main-app. It was important to remember to update import-map.json in Root-app to show system.js where to get the micro-app bundle. If we would replace a regular angular component, we would just need to put an empty <div> in its place and tell single-spa to mount a parcel of the app to this empty element.

But we also had dynamic components in the workspace section, which micro-apps should also replace. In that case, as the first steps, we separated regular dynamic components in the workspace from micro-apps in data that comes from the workspace from the backend.

Now they both have an Id and a type field which helps to determine where we should use a predefined component or dynamic micro-app. In both types, we are loading dynamic component to the workspace area, but for micro-apps, it is the same component that works with the shared parcel utility module and just wrap a micro-app instance.

Here is a diagram of how the mounting flow works in our environment:

We used a trick of import-map to open different components coupled by common logic from one micro-app. It is possible to use a different import-map key for the same micro-app bundle URL. Then on micro-app bootstrap, we got this key value and ran the necessary code. It’s worth noting that if there are multiple instances of the same app, even with different components inside, code like static fields, constants, and environment variables are the same for all instances.

Following this way, we extracted ten micro-apps projects with fourteen main components inside a single-spa environment, fixed hundreds of bugs that single-spa brought us in process, implemented multiple fixes for its internal problems, improved bundle sizes and performance of modules loading, developed the Root-app from a single angular application in the beginning that became an aggregator of multiple single-spa micro-apps in the end:

A Summary of Our Microfrontend Journey

When creating multiple independent apps from scratch, built on different frameworks, using different routes for different app parts, perhaps with old browser support, the choice can be a single-spa environment.

Suppose a large ready mono framework application has multiple modules, tightly coupled components and services, and a lot of shared stuff between application parts. In that case, starting to build a microfrontend application with the webpack module federation approach might be much easier.

Or, when combining different concepts, it is necessary to be prepared to get the downsides of both options.

If you’re interested in adopting a micro-frontend approach for your web application development project, our team would be happy to provide consultation and share our expertise. We have extensive experience using microfrontends to improve development efficiency and deliver high-quality results to our clients. Contact us today to learn how we can help you achieve your web application development goals.

Artificial Intelligence revolutionized how industries and businesses operate with hundreds of innovative use cases. However, implementing an AI project can be complex and challenging despite its potential benefits. According to studies, 70% of companies report minimal or no impact from AI, while 87% of data science projects never make it into production. It highlights the significant obstacles companies face in developing Artificial Intelligence solutions.

In this article, we will explore the common pitfalls of AI projects and how Artificial Intelligence consulting services can help to overcome them. By understanding these challenges, companies can take proactive steps to ensure the successful implementation of AI solutions and realize their full potential.

Unclear Business Objectives

Unfortunately, companies often jump into AI simply because they think they should be doing it, without fully understanding what problem they want AI to solve. Even when a company has a clear idea of its needs, it may choose the wrong problem to solve first, or the scope of the problem may be too large to be fully solved in a reasonable amount of time.

The key to avoiding these pitfalls is looking at the most urgent business priorities and then assessing the resources required to solve them. AI projects should not start with the data at hand and then try to find a problem to solve, as this often leads to science experiments that may not address business challenges.

Instead, it’s important to ask critical questions before launching a project, such as: Is this problem urgent? Why is AI the right solution? How will success be defined? AI strategy consulting company can help clarify business objectives and ensure that AI projects are aligned with the most pressing needs.

Cold Starts

Cold starts are a significant challenge in AI projects, as the performance of an AI system is mainly dependent on the availability and quality of data. The infamous “cold start problem” refers to the situation where an AI system doesn’t have enough data on its users, resulting in poor performance and ineffective recommendations. It can be a major issue for organizations, leading to a poor user experience.

One solution to the cold start problem is to find relevant data that can be used to train the AI system. It can include anonymized data from public sources, which can be structured in a way that the AI can leverage a pre-existing understanding of user characteristics and capabilities. As Artificial Intelligence consultants, according to our DIET framework for AI project development, we define and prepare the necessary amount of data to make effective recommendations without having to wait for the system to collect enough data over time.

Poor Data Quality

Poor data quality is another one of the challenges in AI projects, as it can result in dangerous outcomes if used in decision-making. Before embarking on an AI project, ensuring that the data collected is sufficient, relevant, and comes from reliable sources is crucial. The data should also be labeled correctly and suitable for the AI tool deployed.

One way to address the data quality problem is to know what data you already have and compare that to what data the model requires. It requires knowledge of the types and categories of data you have, whether it is structured or unstructured, and whether you have collected data about your customers’ demographics, purchase history, and on-site interactions, among others. AI technology consulting firms can help companies understand what types of data they need, how to acquire it, and how to integrate it into their AI system.

Implementation Challenges

One of the biggest pitfalls in implementing AI is the need for proper infrastructure for the development and deployment of AI/ML models, software, and applications. The transition from an academic setting, where machine learning is primarily research-focused and solves problems under controlled conditions, to a business setting requires a more complex infrastructure.

This is where Artificial Intelligence consulting services comes into play. As consultants with expertise in AI and machine learning, we can provide crucial support in overcoming the challenges of AI implementation. We help businesses to evaluate their current systems, assess their needs, and design an infrastructure that supports the development, deployment, and operation of models.

Unrealistic expectations about AI

Despite its many advantages, AI is not a magic solution to all problems. One of the greatest misconceptions about AI is that it can take any data and produce results. However, the results’ quality depends on the quality of the data fed into the system. Just like a human, AI works based on the input it receives. Therefore, manual data processing is necessary before starting any AI project.

It is also essential to remember that AI is not a perfect solution and that no neural network works with 100% accuracy. AI is just an assistant that needs to be monitored and corrected if it makes mistakes. Therefore, in IT consulting, we help businesses understand AI’s real applicability in their operations and how much it can help.

Implementing AI projects can be challenging due to various pitfalls, such as unclear business objectives, cold starts, poor data quality, implementation challenges, and unrealistic expectations. At Exposit, we provide AI strategy consulting to help you overcome these challenges, successfully implement your idea, and transform your business. Contact us today to learn how we can support your AI journey.

AI Projects Pitfalls and How Consulting Can Help to Overcome Them was originally published in Predict on Medium, where people are continuing the conversation by highlighting and responding to this story.

We are pleased to announce that Exposit has passed the ISO 27001:2013 and ISO 9001:2015 certifications. These certifications allowed us to upgrade the level of our information security and quality management systems, bringing them into line with international standards to strengthen a partnership with our clients.

Why ISO 27001 and ISO 9001 Certifications Are Essential for Software Development Providers?

ISO 27001:2013 is a standard for keeping sensitive information safe. It includes a comprehensive set of requirements for protecting information from unauthorized access, disclosure, alteration, or destruction. The certification shows that we maintain our clients’ confidentiality and the operations’ security.

On the other hand, ISO 9001:2015 is a standard for quality management systems. It provides a framework for ensuring that a company’s processes are efficient, effective, and aligned with customers needs. The certification guarantees our clients that we deliver consistently high-level services and are committed to continuous improvement.

How Did ISO Certifications Affect the Exposit Processes?

In order to ensure compliance with international standards, we’ve developed policies for smart information security management in accordance with ISO 27001. It includes personal data protection, access rights, password policies, policies for using e-mail and mobile devices, anti-virus policies, and others. Also, we builded quality management systems based on ISO 9001 standard for our agile software development, testing, business analysis, and design.

“We are constantly working to improve Exposit processes and management, paying great attention to the quality of our services and the security of our and clients’ assets. We’ve developed Quality Management and Information Security Management Systems for these purposes. They meet the requirements of the international standards ISO 9001:2015 and ISO 27001:2013, and certificates confirm it.

When building these systems, we chose an area corresponding to our main activity: business analysis, software development and testing, design. We identified the strengths of processes, growth areas, and risks associated with the external environment. Considering these factors, we’ve designed activities reducing software development risks to improve the quality of our services and customer satisfaction.

As for information security, it is a primary requirement of the market. Our customers must be confident that their data is securely protected and won’t be passed on to third parties.”

Dmitri Kuchinski, Chief Operating Officer

What Benefits Do ISO Certifications Provide for Our Clients?

ISO certifications give our clients confidence in the software products and services they get. They can rely on us as a robust partner and entrust their sensitive information. Also, they can ensure our services are of the highest quality level as we adapt our processes according to international standards.

We strive to exceed our clients’ expectations and help them solve their challenges in the best possible way. Contact us to learn more about how our team can help you achieve business goals with Artificial intelligence, Automation, AR/VR, and custom software solutions.

FIFA World Cup is one of the most prestigious soccer tournaments. Throughout the years, it has seen some of the greatest players in the game’s history. From Brazilian legend Pele to German star Miroslav Klose, the world’s most talented footballers have graced the championship.

The best players owe much of their success to their coaches, who identify potential champions, nurture their talent, and guide them toward peak performance levels. A talented coach certainly has a unique intuition but must also have the necessary skills and convenient tools to accurately assess and evaluate the strengths and weaknesses of each team member to develop strategies that can bring victory.

For example, one of the Fifa World Cup favorites, Lionel Messi, began his journey to the top when he was just a young boy. Born and raised in Argentina, Messi was discovered by sports agents at the age of 13. At that time, he played for a local club called Newell’s Old Boys. The agents and coaches were impressed with Lionel’s natural talent. They offered him to participate in a tryout in the youth academy of one of the biggest clubs in Spain, FC Barcelona.

It is clear that Messi’s success came from his hard work and dedication, but it was also driven by his teachers, who saw his potential and took a chance on him. Without agents’ and coaches’ belief in his talent, Lionel Messi may never have become the player he is today.

Data-Driven Talent Identification for Raising New Champions

Football coaches find talents with sports data analytics of past matches, scouting reports from other teams, and player performance metrics. They use a variety of data sources to identify bright football players and determine strategies for winning, for example:

• Game footage.

Game footage is an essential data source that coaches use to evaluate performance and identify key skills of team members. They may also use it to analyze tactics and strategies, looking for opportunities to take advantage of opponents’ weaknesses and improve their own performance. It involves analyzing how teams set up defensively, how they transition from attack to defense, and how they create scoring opportunities. By identifying and addressing weaknesses in these areas, coaches can increase chances of winning matches.

• Statistical data.

Statistical data is crucial for coaches to identify key game trends and patterns. By analyzing data on passes completed, tackles made, goals scored, and other metrics, they can get a better understanding of how players are contributing to the team’s success. This information can be used to inform decisions about player selection, tactics, and strategy.

• Physical data.

Physical data, such as heart rate, distance covered, and sprint speed, can also be valuable for optimizing player results and preventing injuries. By tracking this data during training and matches, coaches can identify areas where players may be struggling and provide targeted support to help them improve. Advanced monitoring technologies, such as wearable devices and GPS tracking, allow coaches to get this data in real-time and adjust as needed.

Peak Team Performance with Computer Vision Football Analytics

Computer Vision football game analysis software is a helpful instrument to process and analyze video data automatically. It extracts relevant information from records, such as player movements, ball trajectories, etc. Then, this data is used to identify areas that need improvement and to develop customized training programs for players and teams. It helps coaches to make informed decisions about player development and team strategy, leading to better performance on the field.

Computer Vision also has the potential significantly scale the scouting capabilities of player evaluation. It allows to quickly and easily analyze large amounts of data, which can be particularly useful for data analyst who may be covering multiple football matches at once. It also could automate specific tasks, such as player tracking and metrics analysis, freeing coaches to focus on other game areas.

For example, Meteor Football Analytics is a pioneering football analysis program designed by Exposit for the football academy to analyze video footage, gain insights into the game, and create individual training. The software uses advanced algorithms to track players’ movements and identify key events in the game, such as passing, intercepting, tackling, etc. and provides detailed progress statistics. This way, it enables coaches to compare the performance of individual players and teams, helping them to make more informed decisions and gain better match results.

The Power of Technologies for Advanced Football Strategy

Computer Vision for football training offers a wide range of advantages. It can be used to track and analyze player performance, identify patterns in tactics, and provide better game understanding from a higher, more strategic level. Additionally, football data solutions allow to simulate game situations, practice specific scenarios, and better prepare for upcoming matches.

Are you looking for the next world-class soccer talent to lead your team to victory? Look no further! Our Computer Vision software, such as Meteor Football Analytics, can help you identify, recruit, and smartly train the top football players with analytics. With our advanced algorithms and deep-learning capabilities, we can quickly and accurately identify the best prospects for your academy. Our experts are ready to develop a tailored Computer Vision solution that meets your specific needs. Contact us today to get started!

How to Find a New “Lionel Messi” and Win FIFA World Cup 2030 with football analytics software was originally published in Predict on Medium, where people are continuing the conversation by highlighting and responding to this story.

Events of the 2022 year capsized the world by waves of war, financial crisis, and natural disasters. Businesses were thrown into a permanent state of uncertainty.

“This uncertainty comes from global shifts not only due to the war in Ukraine — energy price and logistics changes — but also due to earlier accumulated economic imbalances. Key market players: governments, central banks, and big corporations every day make politically charged choices. Imposition of sanctions regarding companies and countries, changes in low, intergovernmental agreements, state programs, and energy security activities strongly impact the business environment and still be very unpredictable.”

Vasili Yavorchuk, Chief Executive Officer

In such conditions, according to statistics in IIA “Risk In Focus 2023” report, internal audit trying to keep companies afloat spends most time and effort on the following top-5 risks:

1. Cybersecurity and data security.
2. Organizational governance and corporate reporting.
3. Change in laws and regulations.
4. Financial, liquidity and insolvency risks.
5. Business continuity, crisis management and disasters response.

Therefore, businesses begin applying conservative, wait-and-see strategies: cut investments into instruments and RnD for development, close IT projects in crisis, optimize costs, and wait until a more predictable environment. On the other hand, a period of tectonic shifts opens a window of opportunities. It can be a good time to bring new products and services to the market and take vacant niches.

So, whether you need to give up developing and implementing new features to your software product in such unpredictable times, or whether it is enough to revise the processes and come up with a crisis management plan? Exposit top leaders shared some insights for IT risk management strategy to guide you through the storm of changes.

Reduce Fixed Costs

Given the need for cost reduction, businesses could consider the removal of permanent staff or a hiring freeze in regions with high expenses. The good option here could be a project development with a reliable service provider: it reduces fixed costs and helps to direct the budget targeted to critically essential projects.

“We offer a way of reducing the directed costs by lower rates and fixed project price, allowing our clients to control the budget accurately.”

Vasili Yavorchuk, Chief Executive Officer

Base Your Decisions On Metrics

Metrics are significant for assessing the progress and understanding the result of IT risk management. Today, analytical instruments and non-financial metrics primarily come into focus: churn rate, cost per lead, lifetime value of the client, etc.

At the same time, it’s important to find software development and maintenance metrics that directly or indirectly influence the company’s finances. For example, if you developed software for monitoring construction materials’ safety, you will naturally reduce manufacturing expenses using it.

Assess The Technical Project Risks

After evaluating all software development possibilities, assessing technical risks for IT project management success is necessary. A trusted IT partner would help you find the most optimal solution or even advise you to cancel a project if the risks of its implementation are not reasonable relative to the expected effect. Also, crisis project management includes revising project plans, optimizing them, and providing solutions for cost reduction or quick hypothesis tests before investing in the development.

“We offer a Discovery Phase to our clients where we work on ideas and test different hypotheses: it allows us to minimize risks the idea won’t work under certain conditions and develop successful it projects.”

Dmitri Kuchinski, Chief Operating Officer

Be Open To Experiments

If your company has a safety margin and a budget for experiments, don’t be afraid to launch it. For staying on track, it’s better to test hypotheses carefully, shorten the product time to market, and realize it into production. In changeable modern world, it is difficult to predict what will work out.

“Today, we see changes in start-ups’ activities and directions of investments; some areas are no longer relevant for the market. Despite the situation, if you don’t get funds into circulation, inflation will destroy them. So, where to invest money? Analyzing the software market, I can say quite promising fields are the development of IoT, ITSM, collaboration tools, and solutions for the automotive industry.”

Aliaksandr Kot, Chief Commercial Officer

Researchers say the key to business survival in 2023 is to be ready for a “continuous storm that will blow through Europe in 2023 and beyond”. It doesn’t mean standing still but carefully going ahead with product development and creating an IT risk management plan.

In Exposit, we’ve prepared our technical and organizational infrastructure for a seamless supply of services. Our teams are located in different countries, company’s legal structure allows to sign contracts with businesses in multiple locations across the world. Technical infrastructure was reorganized for high stability in different scenarios.

We continually enhance the quality of service, processes, and information security and make partnerships with major tech companies (for example, Atlassian). Thereby, we are one of the first to access advanced developments, new instruments, and approaches and successfully use them for IT project implementation.

The company has set up a process for accumulating domain and technological expertise. This way, we can offer the best time-tested solutions based on our experience and be your reliable IT partner with smart risk management at every stage of your software project. Book a free consultation via the link to get crisis management steps and confidently move into the new year.