Thomas uses GenAI RAG on Databricks AI Search to personalize psychometric assessment insights
Thomas, a workplace psychometric assessment provider, used Databricks AI Search and retrieval augmented generation to replace static, one-size-fits-all assessment reports with interactive, personalized query-based insights drawn from its large content database. The GenAI integration became the foundation of Thomas's new 'Perform' product, was integrated into three different platforms including Microsoft Teams within three months, and let the company go from proof of concept to minimum viable product in weeks.
Overview
Thomas, a workplace psychometric assessment provider, used Databricks AI Search and retrieval augmented generation to replace static, one-size-fits-all assessment reports with interactive, personalized query-based insights drawn from its large content database. The GenAI integration became the foundation of Thomas's new 'Perform' product, was integrated into three different platforms including Microsoft Teams within three months, and let the company go from proof of concept to minimum viable product in weeks.
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Inspect the highlighted sourceThe challenge
Thomas's legacy psychometric assessment platform held billions of words of content covering every possible personalized iteration, making it a nightmare to translate evergreen content into useful, tailored responses for each client, and the company still struggled to guide people to the specific content pieces needed to solve their problem.
The solution
Thomas adopted the Databricks Data + AI Platform to improve data ingestion, transformation and analysis, and used retrieval augmented generation (RAG) via Databricks AI Search to let users query the content database directly and receive automatically generated, detailed, tailored insights from unstructured data, integrating the new AI-driven processes into platforms like Microsoft Teams.
Reported business value
Databricks AI Search let Thomas give clients the ability to find the answers they need instead of a 40- to 50-page report, forming the foundation of its new 'Perform' product; Thomas integrated GenAI into three different platforms within three months and went from proof of concept to minimum viable product in weeks.
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