Consumer GoodsRetrieval-Augmented GenerationPublic Cloud

Empowering Marketing Teams to Drive Greater Impact at Reckitt

ReckittDatabricks Data + AI Platform · Databricks Model Serving · OpenAI ChatGPT-4 +3

Reckitt built an AI system called the Insight Engine on the Databricks Data + AI Platform, unifying consumer research, product reviews and social listening signals to give marketing teams faster, actionable insights. The system uses Databricks Model Serving to deploy multiple LLMs including OpenAI's ChatGPT-4 and Google's Gemini, AI Search for retrieval-augmented generation, and Agent Bricks AI Gateway for governance. Reckitt's marketing teams achieved a 40% improvement in task execution, a 40-60% reduction in time to develop campaign concepts, 60% faster concept development, and 30% faster ad adaptation and localization, with hundreds of marketers using the AI tools across the organization by the end of 2025.

Overview

Reckitt built an AI system called the Insight Engine on the Databricks Data + AI Platform, unifying consumer research, product reviews and social listening signals to give marketing teams faster, actionable insights. The system uses Databricks Model Serving to deploy multiple LLMs including OpenAI's ChatGPT-4 and Google's Gemini, AI Search for retrieval-augmented generation, and Agent Bricks AI Gateway for governance. Reckitt's marketing teams achieved a 40% improvement in task execution, a 40-60% reduction in time to develop campaign concepts, 60% faster concept development, and 30% faster ad adaptation and localization, with hundreds of marketers using the AI tools across the organization by the end of 2025.

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The challenge

Reckitt's marketing teams had long relied on fragmented systems and traditional, manual workflows; marketers could spend weeks combining data from multiple sources even for routine tasks like media analysis or brand performance reports, leaving little time to adapt to market changes and focus on innovation. Reckitt needed a unified platform to handle both structured and unstructured data across multiple functions while ensuring scalability and governance.

The solution

Building on their existing use of Databricks for data warehousing and structured data, Reckitt extended the platform to power its GenAI ambitions, building an AI system called the Insight Engine that unifies consumer research, product reviews and social listening signals. At the core of the architecture is Databricks Model Serving, giving real-time access to multiple LLMs including OpenAI's ChatGPT-4 and Google's Gemini tailored to different business needs. AI Search, a retrieval-augmented generation component, retrieves relevant information from structured and unstructured sources to power the Insight Engine, while Agent Bricks AI Gateway provides integrated governance so AI outputs remain reliable and safe while scaling.

Retrieval-Augmented GenerationGenerative AIRecommendation & PersonalizationAgentic AI

Reported business value

Reckitt's marketing teams achieved a 40% improvement in task execution and a 40-60% reduction in time to develop campaign concepts, including 60% faster concept development and 30% faster ad adaptation and localization. Marketing teams can now analyze data in days instead of weeks, and hundreds of marketers were using the AI tools across the organization by the end of 2025.

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