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 05

Quality control monitoring agent

Runs on a schedule across the website, publications, and social channels. It catches broken links, off-brand assets, and factual inconsistencies, then files each one with a suggested fix. Nothing is changed automatically.

Our play for this Web and social connector, out of the box
1We have done this
Retail and consumer brands
We run always-on monitoring engines that scan public sources and flag what matters.
See our track record
2What we need from you
  • Read access to the sites and social accounts
  • Your brand kit and style rules
3How we implement
  • Schedule the crawler across web and social
  • Load your brand and link rules
  • Send a nightly digest to Teams or Slack
4Live on your data
about 1 to 2 weeks
Then we validate together and move to the next use case.
ArchitectureWeb + publications + socialNightly scan agentFindings + fixesDigest to your team
See it working, with mock data

Last scan ran 6 days ago

Run an on-demand scan across web, publications, and social.