SLB: Putting data & AI to work for energy

SLB's data lived in unstructured reports, tender-response windows were extremely tight, and manual processes across business functions were error-prone. It partnered with Dataiku to let domain experts and data scientists build automated workflows with no-/low-code tools while keeping control over outcomes. In well-construction tenders, analysis time fell from 8 hours to 20 minutes across more than $10 billion in assessed tenders; reservoir pressure analysis saw a 76% efficiency improvement with automated stabilized-pressure identification; and predictive attrition modeling plus a Skills2Career Dashboard retained an estimated $18-45 million annually while cutting external recruitment costs by hundreds of thousands. President Rakesh Jaggi said 'billion dollar decisions are now data driven, while keeping our well engineering experts in control of the outcome.'

Dataiku is a low-code/no-code AI platform whose Prompt Studios and LLM Mesh let teams prototype and A/B-test candidate LLM approaches before committing to a production workflow.

This sits in the Design & Stress-Test stage of the AI use-case lifecycle: Named examples from the tools pharma teams use to scope, prototype and benchmark an AI use case before committing to build it — data-catalog, sandbox and evaluation platforms.