Agentic AI Analytics Platform for a Luxury Jewelry Brand
Challenge
Executives relied on analysts to access sales, inventory, and customer data across fragmented systems, making business insights difficult to obtain quickly. Report generation took 48–72 hours, while static dashboards limited real-time visibility into business performance. The organization needed a centralized, intelligent analytics platform that could simplify data access, automate reporting, and enable executives to make faster, data-driven decisions without depending on technical teams.
Executives relied on analysts to access sales, inventory, and customer data across fragmented systems, making business insights difficult to obtain quickly. Report generation took 48–72 hours, while static dashboards limited real-time visibility into business performance. The organization needed a centralized, intelligent analytics platform that could simplify data access, automate reporting, and enable executives to make faster, data-driven decisions without depending on technical teams.
Solution
Developed an agentic AI analytics platform that lets executives query business data in natural language. Integrated an LLM with Snowflake, built intelligent schema mapping and SQL generation, implemented Azure AI Foundry orchestration, and added query logging, role-based access control, and feedback-driven learning.
Developed an agentic AI analytics platform that lets executives query business data in natural language. Integrated an LLM with Snowflake, built intelligent schema mapping and SQL generation, implemented Azure AI Foundry orchestration, and added query logging, role-based access control, and feedback-driven learning.
Results
Reduced insight delivery time from 48–72 hours to under 5 seconds, enabling executives to access business insights almost instantly. Automated analytics freed 60% of the analytics team's capacity previously spent on manual reporting, allowing analysts to focus on strategic initiatives. The platform also achieved over 85% user adoption within six months, improving data accessibility, operational efficiency, and executive decision-making across the organization.
Reduced insight delivery time from 48–72 hours to under 5 seconds, enabling executives to access business insights almost instantly. Automated analytics freed 60% of the analytics team's capacity previously spent on manual reporting, allowing analysts to focus on strategic initiatives. The platform also achieved over 85% user adoption within six months, improving data accessibility, operational efficiency, and executive decision-making across the organization.