Architecting & Engineering Production-Grade Agentic AI for Industry-Specific Needs

Agentic artificial intelligence (AI) systems are increasingly adopted across industries, yet each industry brings its own regulations, users, data and ways of working. A general-purpose chatbot built on a large language model cannot meet these needs on its own; the system around the model has to be designed for the industry it serves. This paper presents a cross-domain practitioner study of four Agentic AI systems that were architected, engineered and deployed by the Author and are presented together in Rimjhim AI Kingdom®, a navigable web ecosystem in which each system appears as a building in a virtual city. The systems serve banking, residential property, hotel review management and e-commerce customer service, and were developed in Python without the use of any no-code or low-code platforms. For each system, the paper traces how the needs of the industry shaped the architecture. Comparing the four systems, it identifies six customisation dimensions along which an AI architect adapts a shared agentic core: interaction mode, knowledge source, reasoning style, compliance layer, integrations and the boundary of automation. The paper argues that these decisions belong to the AI architect and engineer, and it draws design lessons for building industry-specific agentic systems.