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It hasn’t been long since AI tools like ChatGPT turned from a curiosity into a standard part of the business toolkit. Today, the real question is no longer whether to try them, but how to make them work for your goals.
Some companies are still hesitating, worried about risks, costs, or uncertain ROI. Others are moving ahead — integrating AI into their products, streamlining processes, and finding new ways to engage customers. The difference between these two groups is only getting more noticeable.
Oxagile is firmly in the second camp. We actively use ChatGPT for business, applying its capabilities in client solutions and internal workflows, while keeping a close eye on new updates to spot opportunities for even greater value.
Let’s take a look at how ChatGPT is already transforming products and operations — with real-life use cases that might inspire your next move.
Since our clients recognize the value of ChatGPT, we have already expanded our portfolio with a variety of real-world use cases — from customer support automation to content optimization, ChatGPT-powered analytics, document automation, and multimodal AI features that combine text, images, and voice.
Let’s go through some of these projects one by one.
A key component of the language learning app we created was a peer-to-peer interactive forum where students could complete tasks and share their answers for feedback from other learners — from grammar corrections to vocabulary suggestions. Despite its simplicity, this feature played a crucial role in communication, motivation, and knowledge exchange.
Some exercises didn’t receive timely responses, which slowed interaction and reduced user engagement. Unanswered posts also discouraged participation, as students became less motivated to submit their work.
To solve this, we implemented a ChatGPT-based bot. If an exercise didn’t receive feedback from another user within 5 hours, the bot automatically provided constructive comments and corrections. Over time, the model was refined using the platform’s own correction history, ensuring that the feedback matched the tone, teaching style, and accuracy expected by the learning community. This approach improved engagement and helped sustain a supportive environment.
A learning platform offering general programming education, which creates almost all explanatory materials in manual mode, has been placing significant emphasis on tests and quizzes after each lesson to reinforce knowledge and encourage active learning.
There was a significant churn rate after 3–5 lessons. Analysis showed that many students were frustrated by the large number of tricky, misleading, or overly complicated questions in the tests. While such questions can be effective in certain contexts (like driver’s exams), they proved counterproductive for a platform focused on motivation and long-term engagement.
We collected samples of quiz questions from instructors and trained the model to categorize all platform questions into “suitable” and “potentially discouraging.” ChatGPT now assists in identifying overly complex or misleading questions and suggests simplified, clearer alternatives that align with the course’s learning goals. This process improved user retention and helped maintain a balance between challenge and accessibility.
A learning management system (LMS) used by one major technological company was constantly expanding its content, carrying out ongoing skills testing for employees, and, following the principle of continuous education, enriching the existing courses with fresh materials.
The release of new courses was frequently delayed. Educators needed to prepare large volumes of exercises manually, which slowed content production and limited the platform’s ability to keep up with learners’ demand. There were concerns that automating the process might harm quality, resulting in illogical or inconsistent exercises.
For certain types of courses included in this LMS, especially language learning ones, integrating ChatGPT has proven to be an excellent solution saving time and allowing teachers to focus on delivering the lessons rather than compiling similar exercises.
This way, for instance, ChatGPT now generates human-like, high-quality personalized questions for students where it is necessary to reinforce a specific topic or rule.
The owners of a retail chain examined customer reviews and feedback every day to identify recurring patterns in different aspects of the business and find areas for improvement.
While manually looking through the reviews was wasting a lot of time and, most importantly, human resources, we implemented sentiment analysis, using the Amazon Web Services tool, to understand the semantics of a review (whether it was “positive”, “negative” or “neutral”).
But the challenge persisted, as there were loads of aspects covered and evaluated. Besides, a single review could contain positive feedback about the product quality, and negative about customer service, which made it hard for the tool to analyze the details.
To separate reviews by subject and differentiate information in one single review, for example, about the satisfaction with the products offered, staff friendliness, and a store’s atmosphere, we implemented a meticulous ChatGPT prompt. It now processes the reviews together with the AWS tool and provides structured data ready for analysis and data-driven insights.
A small part of the services provided by a brand reputation monitoring company is tracking consumer reviews, actively engaging with customers, and addressing objections to boost their clients’ ratings.
Many clients who availed themselves of the company’s services, which also encompass tasks such as managing business accounts, crafting posts, and elaborating business strategies, expressed a desire for some cost reductions without compromising the quality of service. In response to this, the company considered a few business ideas and identified an area where they could help clients save money: automating the process of answering their comments and reviews.
We integrated the ChatGPT model with the platform via API, allowing clients to input customer reviews and get suggested responses. While responses can still be manually refined, the process became faster. ChatGPT provides personalized replies, helping maintain customer satisfaction without extensive manual effort.
If you doubt whether ChatGPT is good for handling your tasks and solving your challenges, we are delighted to show you how to get the most out of this AI tool, rather than just using it to follow the fashion.
ChatGPT is also slowly but surely reshaping the way Oxagile staff perform routine as well as non-trivial tasks. Here are the most popular examples of how we, as well as our clients, take advantage of OpenAI capabilities to facilitate business operations.
It’s hardly a revelation that ChatGPT can be used as a more convenient version of Google, that won’t make you dig into Stack Overflow or similar forums for a solution lost somewhere in the endless pages. When interacting with ChatGPT, spotting a mistake in a piece of code will boil down to copy-pasting it and asking the AI chatbot for a diagnosis.
And though sometimes the information that ChatGPT has been trained on may not be enough to notice a mistake, our experience shows that in many cases it still serves as a reliable alternative to static code analyzers.
Let’s take the liberty of noting that a considerable part of programming consists of compiling ready-made code parts that were written by someone else and adjusting the result to your specific usage. And according to our developer’s feedback, ChatGPT perfectly copes with this task, saving time on searching for code snippets on other sites. However, it is important to understood that asking ChatGPT to solve problems that no one has solved yet is a dead end. At least for now.
When there are technical specifications of the project that need to be presented to the client, so that he does not get bogged down in specific jargon, or persuasively describe the need for migrating data to microservices to the manager, who probably sees this combination of words for the second time in his life, ChatGPT is great to concisely reformulate all technical data into an exciting story.
In case there’s a project coming up that requires brushing up on tools used some time ago or figuring out what new features have appeared in familiar programs, we take advantage of the brilliant ChatGPT ability to create step-by-step learning plans and programs specifying resources and materials that are worth checking out depending on specific goals.
ChatGPT allows our QA engineers to speed the test lifecycle and reduce the QA workload by 5–6 times by generating unit tests based on the context and the desired outcome. It quite clearly analyzes given requirements and provides good results, creating competent tests that help to avoid the accumulation of errors and free up time for our QA team members to perform a range of other crucial tasks.
ChatGPT is also a nice source of inspiration for our project managers at a stage when a lot of functionality has already been implemented in the project, but we still want to enhance it. In these cases, we provide ChatGPT with the project context and vision, and use its suggestions as a starting point. Combined with other brainstorming tools, this helps generate new feature ideas that can later be refined into valuable upgrades.
Oxagile event managers keep filling our calendars with the conferences suggested by ChatGPT, as it proved to be quite useful in determining the ones that were seemingly unrelated to our field of expertise, but still had potential for our company to make connections and develop new business ideas. To increase accuracy, ChatGPT is now often used together with event search plugins or integrated APIs, which makes the recommendations more relevant and up to date.
Life is too short to read the whole user agreement. Basically, just like any other lengthy text, ChatGPT agrees with this statement and easily provides brief summaries of specialized articles, highlighting what our team members ask it to single out or answering questions about the content of the document provided. This is probably one of those business use cases for ChatGPT that we enjoy across almost all departments.
Despite the fact that ChatGPT is quite a creative companion, entrusting it to craft meticulously optimized SEO articles may be quite a risky thing to do. However, seeking its assistance to write a list of keywords relevant to your topic or even analyze your competitors to understand the competitive landscape is a reasonably achievable task. The main thing is to clearly outline the task you have in mind, and ChatGPT will come up with a comprehensive list.
Our HR managers proved that ChatGPT can be turned into a tool that helps develop in-depth interview questions for an expert in practically any field. By providing details, such as job requirements and the essential hard skills expected from an ideal candidate, ChatGPT compiles a set of open-ended questions that may include various aspects, like problem-solving scenarios, which aim to evaluate the knowledge and capabilities of individuals possessing the specified expertise and experience.
With multimodal capabilities, ChatGPT can work with text, images, tables, and charts in a single workflow. For example, a marketing team can upload a PDF report with visuals or an Excel file with raw data, and ChatGPT will generate summaries, highlight key trends, and suggest actions based on the analysis.
ChatGPT can help legal and finance teams monitor compliance by reviewing contracts, documents, and procedures for alignment with corporate policies and regulatory requirements. It can flag risky clauses, inconsistencies, or potential violations for further human review, speeding up the compliance process.
Integrated with conferencing tools like Zoom or MS Teams, ChatGPT can create concise meeting summaries and structured action lists. It captures key decisions, follow‑up tasks, and responsible parties, helping project managers, HR, and sales teams keep track of commitments.
ChatGPT can be used to analyze the tone of customer communications across support chats, emails, and social media. Negative messages can be automatically escalated to senior support staff, while positive feedback can be flagged for marketing or case study opportunities.
Working alongside translation memory systems, ChatGPT helps adapt marketing content to multiple markets with cultural sensitivity. Campaigns, product descriptions, and user documentation can be localized faster and more accurately without compromising brand voice.
The use cases above show that ChatGPT has moved far beyond simple Q&A interactions and now works as a flexible tool across business domains — from eLearning and retail to compliance, localization, and internal process optimization.
Our experience proves that AI integration brings the greatest value when applied to well‑defined, relevant tasks, where automation improves efficiency, accuracy, or customer experience.
Rather than adopting ChatGPT features just to follow a trend, it is worth focusing on areas where it can make a measurable impact on products, services, and operations.
If you are ready to explore how AI-powered innovations can strengthen your business, Oxagile can help identify the most promising scenarios and implement them in a way that delivers long‑term results.
While ChatGPT may seem ready to answer any question, ranging from philosophical inquiries to practical programming tricks, it itself often sparks quite intriguing questions from those who reach out to us seeking its implementation in their businesses. Here are the answers to some of them.
It’s hard to choose just one example that stands out among the variety of great ChatGPT use cases for business. However, from our point of view, providing natural language replies in response to users input is probably one of the most valuable ChatGPT functions that saves the company’s money and resources, while also increasing user loyalty and trust.
As the algorithm of this natural language processing tool was trained on a very large data set, it not only understands how meaningful human speech works to be able to conduct conversations, but is also perfectly suited to create useful and informative materials. At the same time, it often uses patterns and templates, making the content it produces quite recognizable and repetitive. And there is a chance that some of the massive amount of data on the internet that ChatGPT has been trained on has been biased or incorrect. Therefore, it is often crucial to fact-check when using this AI tool.
However, it should be noted that correctly drafted prompts, specifying important conditions and telling ChatGPT how to act, minimize these kinds of issues.
ChatGPT can work with business‑specific data, but it’s important to ensure that the integration respects security and compliance requirements. Many companies use private deployments (such as Azure OpenAI or AWS Bedrock) to process data securely within a controlled environment.
ChatGPT can be integrated via API into CRMs, ERPs, collaboration tools, and custom software. It also works in combination with event search APIs, translation memory systems, and data analytics platforms to expand its functionality beyond standalone chat interactions.
Yes, in scenarios like customer sentiment monitoring, automated meeting summaries, or instant compliance checks. However, its performance depends on the infrastructure, integration setup, and the complexity of the requested task.
