Why CatBoost, Not LLM? Choosing the Right AI for Business Impact

Many organizations today are exploring how to integrate Large Language Models (LLMs) into their workflows. However, my experience shows that often the most accurate and profitable solution to a current business challenge isn't necessarily an LLM, but rather smart use of existing data.

The Hidden Value in Structured Data

Most of the substantial business value in companies lies in structured data — and there's a lot of it: CRM systems, transaction data, transfers, purchases, sales, endless operational logs, and more.

To extract the business potential from this data, our choice is often CatBoost.

What is CatBoost?

For those unfamiliar, CatBoost is an ML algorithm specifically designed to handle categorical data (such as product types or customer IDs) naturally, without requiring complex pre-conversion.

Why is This Tool Super Relevant in 2025?

While the technology frontier is primarily focused on GenAI, the business world still runs on tables. In this world of precise data, CatBoost provides a dual advantage: it requires minimal manual "data engineering" and delivers prediction accuracy that often surpasses more complex and newer solutions — in a fraction of the development time.

The INUXO Approach

At INUXO, our approach is to always adopt only AI solutions that generate measurable business impact. Choosing mature and efficient technology like CatBoost allows us in many cases to achieve significant value, save expensive development resources, reduce costs, and focus on what really matters — clear value, not experimentation.

When to Choose CatBoost Over LLM

• Your data is primarily structured (tables, databases, logs)
• You need high prediction accuracy for classification or regression
• Fast time-to-value is critical
• Development resources are limited
• The business problem is well-defined with clear metrics

Conclusion

Before jumping on the LLM bandwagon, take a step back and assess your actual business challenge. The answer might already be sitting in your existing data, waiting to be unlocked with the right tool. Sometimes, the most innovative choice is the most practical one.