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Case Study: Novartis streamlines analytics and AI with a 90% reduction in time to insights using Dataiku

Novartis Case StudySourced & dated by Case Study Desk
Key facts · TL;DR
Company
Novartis
Industry
Life Sciences
Challenge
Slow, manual analysis of research data
Headline result
90% reduction in time to insights

Key results

90%
Reduction in time to insights
GenAI use case · 21 days to 2
600%
Acceleration in data ingestion time
Spreadsheet use case · 1 week to ~6 hours

The challenge

Novartis conducts extensive healthcare market research, generating large volumes of interview data, but analyzing hundreds of 20-page transcripts was tedious and time-consuming, slowing insight extraction. Building a GenAI chatbot to address this typically follows a lengthy product-development lifecycle, and separate spreadsheet-based reporting relied on manual weekly calculations.

The solution

Novartis used Dataiku's LLM Mesh and GenAI builder capabilities, including Prompt Studios, Dataiku Answers, and LLM-powered recipes, to build a retrieval-augmented chatbot and automate spreadsheet-based analytics. LLM monitoring via Dataiku's scenario and bundle capabilities supported oversight and governance across applications.

The Dataiku LLM Mesh offers substantial strategic benefits, notably accelerating time to market for GenAI chatbot development, reducing costs, and mitigating risks associated with LLM provider dependencies.

DS
Deepthi Sanam
Group Lead, Data Engineering, Novartis

The results, in context

Novartis reports a 90% reduction in time to insights on the GenAI use case, from 21 days to two. In its spreadsheet use case, the company reports a 600% acceleration in data ingestion time, from a week to about six hours.

Products used

Dataiku LLM MeshDataiku Prompt StudiosDataiku Dataiku AnswersDataiku LLM-powered recipes