This paper presents the design of a new system for dynamically adjusting safety stock levels based on real-time data. The proposed system addresses the challenge of balancing service level targets and financial constraints in inventory management. Service level targets, directly influencing safety stock levels, aim to ensure a high probability of meeting customer demand. However, financial constraints, such as budget limitations and cash flow considerations, impose restrictions on the amount of capital that can be allocated to inventory. To tackle this problem, in this research, the proposed system utilizes ABC classification to identify high-volatile items and prioritize them in the adjustment process. The goal is to minimize inventory costs while maintaining desired service levels, thus optimizing the allocation of capital and enhancing overall inventory management efficiency. The efficacy of the proposed model is demonstrated through a sample numerical data analysis, providing empirical validation of its effectiveness in real-world scenarios. We were able to create a model which can a) re-distribute the cycle service level value based on the required budget using linear programming and prioritizing high-volatile items, b) analyze various scenarios in regards to demand lead-time variations.