AIInsightsCopilot
Natural language interface to internal & external data
Overview
An Agentic AI Insights Copilot that triangulates internal (sales, profit, trade) and external (NIQ/Circana) data to explain performance, surface drivers, and recommend next best actions.
Key Metrics
Case Study
The Problem
Answering "why did our performance change?" required hours of analyst work triangulating internal sales data with external syndicated data. Non-technical stakeholders were completely dependent on analysts for even basic performance questions.
The Approach
Built an agentic AI that connects internal systems (sales, profit, trade) with external sources (NIQ/Circana) — asking one question queries both simultaneously
Designed a natural language interface so anyone — brand managers, sales directors, finance partners — can ask questions without knowing SQL or data schemas
Agent reasons across data sources to surface root causes of performance changes and suggest specific next actions
Optimized for non-technical stakeholders: outputs are narratives and recommendations, not raw data tables
The Impact
Dramatically reduced time from question to insight — what took hours of analyst work now takes seconds
Unlocked self-service analytics for non-technical stakeholders who previously waited days for answers
Moves the team from descriptive analytics (what happened) to prescriptive (what to do next)
More projects