<![CDATA[This study aims to enhance the efficiency of inventory management, order processing, and stock requirement forecasting for a distribution company. The primary challenge addressed is the reliance on manual record-keeping systems, which frequently lead to delays, recording errors, and difficulties in decision-making. The Software Development Life Cycle (SDLC) methodology was employed to plan, develop, test, and implement the software. The system incorporates intelligent inventory features leveraging the Nixtla and OpenAI APIs to generate stock requirement predictions, alongside a warehouse-integrated online ordering system that utilizes the Midtrans API as a payment gateway to streamline transactions and ensure automated payment verification. Black-box and user testing demonstrated that all functions operate according to specifications; the system accelerates inventory recording to a maximum of one minute, thereby increasing efficiency, simplifying order management, and assisting stock managers in making data-driven procurement decisions. Consequently, this research offers a viable solution and contributes to the integrated digitalization of distribution companies.]]>
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