How HP Built a GenAI Data Chatbot in 3 Weeks Using Databricks Mosaic AI to Recover 20-30% of Data Team Time
HP, the global computing and printing company managing data products for 200+ million printers worldwide, deployed Databricks Data Intelligence Platform on AWS to unify customer data ingestion across business units and build an internal GenAI data chatbot. Using Databricks Mosaic AI, DBRX, Unity Catalog, and AI/BI Genie with a RAG architecture, HP built the chatbot in under three weeks — recovering 20-30% of data team time previously spent on manual SQL queries, achieving 20-30% cost savings versus AWS Redshift, and enabling 600+ Databricks users across the organization.
Impact
20-30%
Cost savings vs AWS Redshift
20-30%
Data team time recovered from manual SQL queries
3 weeks
Time to build GenAI data chatbot
600+
Active Databricks users
Challenge
HP's data teams spent significant time on manual SQL queries to answer business questions across complex customer datasets from 200+ million printers worldwide — creating bottlenecks, consuming engineering capacity, and leaving non-technical stakeholders unable to self-serve data insights.
Solution
HP deployed Databricks Data Intelligence Platform on AWS with Unity Catalog, Vector Search, and Mosaic AI, building a GenAI data chatbot using RAG architecture and the DBRX LLM — enabling natural-language data queries for 600+ users and eliminating routine manual SQL work within three weeks of development.
Tools & Technologies
What Leaders Say
“This solution has quite a few pieces...The college intern implemented the end-to-end solution in less than three weeks.”
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Full Story
HP manages data ingestion and customer data products at a scale that few organizations match — with more than 200 million printers worldwide generating telemetry and customer signals across multiple business units. Analysts and data teams were spending significant time on manual SQL queries to answer business questions, creating a bottleneck that slowed decision-making and consumed engineering capacity.
HP standardized on Databricks Data Intelligence Platform running on AWS to centralize data operations. The team implemented Unity Catalog for data governance and discoverability, Databricks SQL for analytical queries, and Vector Search for semantic retrieval across internal datasets. The platform gave HP a foundation to run large language models natively within the data environment — without exporting data to external AI services.
The breakthrough moment came when HP's team built an internal GenAI data chatbot using a RAG (Retrieval-Augmented Generation) architecture powered by Databricks Mosaic AI and the DBRX large language model. The chatbot allows analysts and business stakeholders to query HP's internal data in natural language — replacing manual SQL for routine questions and freeing data engineers to focus on higher-value work. As William Ma, HP's Data Science Manager, noted: "This solution has quite a few pieces...The college intern implemented the end-to-end solution in less than three weeks."
The impact was measurable across cost and productivity dimensions. HP achieved 20-30% cost savings versus its previous AWS Redshift environment. The chatbot recovered 20-30% of data team time that had been spent on manual SQL queries. The platform now supports 600+ Databricks users across HP's global business units, with AI/BI Genie enabling self-service analytics beyond the traditional analyst team.