Carnegie AI PlatformConcept by The PRR Group
Live demonstrations

The same four steps for every use case

We took the seven use cases you gave us, matched each to work we already run for existing customers, and built a working demo on mock data. Every one follows the same play: we have done it before, here is what we need from you, here is how we build it, and here is how fast it goes live. See it work, tell us what to change, and we move to the next.

Runs where your team already works: In Microsoft Teams On your platform Single pane of glass
01Concur receipts02Library research03Contact / CRM04China AI KMS05QC monitor06Event logistics07Ask Andy
Use case 02

Library research agents across journals

Carnegie's library holds shared accounts to many journals, and scholars sign into each one separately. This agent uses those credentials to search, retrieve, and summarize across all of them from a single question.

Our play for this Library and journals connector, out of the box
1We have done this
R1 research universities
We build multi-source research platforms with the University of South Florida.
See our track record
2What we need from you
  • The library's existing shared journal accounts
  • Which databases to include
3How we implement
  • Store the shared credentials in the vault
  • Connect the subscribed databases
  • Validate the first results with a librarian
4Live on your data
about 2 to 3 weeks
Then we validate together and move to the next use case.
ArchitectureScholar's questionFederated search agentSummaries + citationsTo the scholar
See it working, with mock data
1A scholar's question
Requested by a scholar in Technology and International Affairs
Signs into: JSTOR Foreign Affairs ProQuest Taylor & Francis SSRN Web of Science