New playbook: when your own AI model pays. Read
CVS Health (healthcare and pharmacy) reported this on 26 Aug 2026 in vendor case with a named customer (source). It belongs to the data and ontology layer.
A Genie-based research agent on Databricks that answers finance and store-operations questions about the labour-demand forecast, with explanations, replacing data scientists answering stakeholder emails.
Weighted MAPE (forecast error) improved 1% in the 2 months after deployment, versus about a year for the previous 1% gain; the speaker values that at roughly $5–10M a year in reduced overtime and overstaffing. Data scientists had been spending ~20 hours a week acting as analysts.
The number covers labour-demand forecasting team; dollar value is the speaker's estimate.
“It took us a year to get there to the other to the last time we improved by 1% before that,” CVS Health said.
Shared definitions of your metrics and records, used by both staff and agents.
Read the guide to data and ontology.
10 minutes
to scope a supply shortage, down from 3 months and 30 people
An enterprise data layer on Palantir Foundry unifying 33 ERPs (~3.5M data connections), feeding a Sector Control Tower for executives and a Program Digital Cockpit for program teams (source).
27 days
faster time-to-sign for candidates
A recruiting and hiring agent in Microsoft Copilot Studio, grounded in the Celonis Context Model (process-mining data on how hiring actually flows), used by recruiters and hiring managers (source).
Days → minutes
for fund-formation analysis and drafting, the firm says
The Fund Formation Engine on Palantir AIP and Ontology, bringing institutional knowledge, data and workflows for private-equity fundraising (documents, side letters, obligations, closings, compliance) into one system for every lawyer (source).