New playbook: when your own AI model pays. Read
Uniper (energy) reported this on 9 Sep 2026 in vendor case with a named customer (source). It belongs to the data and ontology layer.
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.
Average time-to-sign for candidates cut by 27 days; screening phase shortened by 13 days. Before production, the same prompts run on raw HR-system data returned generic answers, while the process-grounded agent named Uniper-specific bottlenecks.
The number covers recruiting and hiring process at Uniper after the agent went to full production; with/without-context comparison was a qualitative side-by-side test.
“With Celonis as our context layer, we’re building AI solutions that aren’t just tools we experiment with,” Uniper 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).
2 months
for a 1% forecast-error gain that last took a year
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 (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).