We successfully created a powerful language model capable of understanding and interpreting regulations from different countries and industries. This model became a valuable tool for importers and exporters, enabling them to assess the products' compliance with regulations in multiple markets swiftly. With the regulations language model in place, our client experienced significant efficiency gains. They could now swiftly identify the necessary adjustments or certifications required to meet specific regulatory standards before entering new markets. This, in turn, reduced compliance-related delays and expenses. By utilizing Kubernetes and Docker for containerization, we achieved cost-effective scalability, ensuring the system could handle fluctuations in demand and data processing requirements efficiently. This approach helped in optimizing cloud resources and minimising unnecessary expenses. Snowflake's data warehouse solution empowered us with enhanced data management capabilities. We could seamlessly organize, store, and analyze vast amounts of regulations data, making it readily accessible for the language model training and future updates. Through the successful execution of this project, SPAR was able to establish itself as a leading provider of Generative AI solutions. The language model of regulations developed with the help of Azure technologies, Scrapy, Databricks, and Snowflake proved to be a game-changer for importers and exporters worldwide. Our commitment to innovation and leveraging cutting-edge technologies allowed us to strengthen our position in the market and provide exceptional value to our clients.