At Itsavirus, we are known for adopting new technologies fast. So, since the early rise of AI, we have been working on several AI projects. In this blog, we’ll walk you through some of the AI-driven solutions we’re working on. After that, we'll talk about the hurdles we’ve faced and the best practices we've discovered along the way. We'll also explain how we’ve used different AI tools for different situations, because every project has its own unique needs.
AI isn't magic—it's the result of combining big data and machine learning. Think of it like teaching a baby to recognize fruits by showing them many examples; over time, they learn to identify patterns. Similarly, in machine learning, a computer is trained with large amounts of data to recognize patterns and make predictions, which is then stored in a "model."
When working with AI tools like OpenAI, choosing the right model (like GPT-4 for text or DALL·E for images) is key, as the output quality depends on both the model and the input provided. Clear and specific prompts are crucial for getting accurate results. AI has various applications, from summarization to personal assistance, but each model has its limitations, such as processing large amounts of text.
In one of our projects, we faced the challenge of transforming large volumes of research data into coherent, human-like reports rapidly. The goal was to develop a system that could analyze raw survey data and produce insightful, visually appealing reports as if crafted by a skilled human writer.
To tackle this, we leveraged OpenAI's GPT-4o-mini model to serve as an "interviewer." Here's how it worked:
The result was a highly efficient process that turned complex, quantitative data into qualitative insights with human-like accuracy and nuance, significantly speeding up the report generation process while maintaining a high standard of quality.
Objective: To efficiently manage and update multilingual content on a large European platform, ensuring timely and accurate translations across numerous languages, particularly for high-traffic websites and real-time customer communications.
Challenge: Managing extensive, multilingual content for a platform operating across multiple countries is a significant challenge. Traditional translation methods are often slow, costly, and prone to inaccuracies, especially when frequent updates are required.
Solution: We integrated ChatGPT, an advanced conversational AI by OpenAI, into our translation workflow.
Implementation:
Outcome: The integration of ChatGPT significantly reduced the time and effort required to manage and update multilingual content. The automated translation process ensured that content was accurate, consistent, and timely, greatly enhancing the user experience and operational efficiency of the platform.
Objective: Our goal was to develop a comprehensive tool that generates highly personalized meal and workout plans by leveraging various personal data points. This tool is designed to cater to individual dietary needs, fitness goals, preferences, and available resources, ensuring that users receive both meal and workout plans that are nutritionally balanced, effective, and aligned with their personal objectives.
Challenge: The primary challenge was to create a system capable of handling the complexity of individual preferences and requirements across both meal and workout planning. We needed an AI that could interpret a wide range of personal data—such as age, gender, fitness level, training intensity, food preferences, location, available equipment, and health goals—and generate plans that felt tailor-made. Ensuring the output was accurate, safe, and user-friendly for both aspects of health management added an extra layer of complexity.
Solution: We utilized Claude.ai, an advanced conversational AI developed by Anthropic, known for its emphasis on safe and accurate responses. Claude.ai's capability to handle complex conversational inputs made it an ideal choice for interpreting diverse and detailed personal data to generate both meal and workout plans. Its flexibility and scalability ensured that the AI could manage a wide array of user requests while maintaining a high level of personalization and precision.
Implementation:
Outcome: The result was a highly efficient, scalable tool that generates personalized meal and workout plans, helping users achieve their dietary and fitness goals with precision. By leveraging Claude.ai, we were able to offer a service that feels deeply personalized, intuitive, and supportive of a healthier lifestyle. The integration of both meal and workout planning in one tool provides a holistic approach to health and fitness, making it easier for users to follow a comprehensive plan that meets all their needs.
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