This paper examines the synergy between Large Language Models (LLMs) and traditional rule-based systems in generating actionable business insights from structured data. The dual approach leverages the predictability of rule-based systems with the adaptive learning capabilities of LLMs, aiming to improve precision in business applications.

• Comparison of methodologies in data handling and insight generation.
• Practical implications for enhanced decision-making.

This study highlights the potential of hybrid systems to revolutionize business analytics, suggesting that such frameworks could deliver more reliable and precise insights, critical in strategic business decision-making.