Five real-world AI use cases from Celonis AI Lab in Columbus
Across five companies at Celonis AI Lab, shared challenges included procurement spend not linked to master catalogs, manual helpdesk operations requiring multiple FTEs, category managers lacking visibility into contract leakage, chargeback teams manually resolving large volumes of daily rejections, repeated manual vendor contact for PO confirmations, and insurance adjusters manually checking compliance documents across multiple states.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Vendor inquiry triggers agent
Upon receiving a vendor inquiry, an agent is triggered automatically.
Tools used
Process CopilotsAnnotation BuilderPrediction BuilderOrchestration EngineLarge Language Model (LLM)
Outcome
Prototype solutions aimed to deliver significant cost savings via catalog conformance, speed up vendor inquiry resolution with improved transparency, automate C-suite Spend Under Management reporting, stop chargeback rejections before they occur, eliminate repeated manual vendor contact, and remove the burden of manually checking insurance compliance documents.
What failed first
Manual random-sampling for insurance compliance revealed blind spots in regulatory adherence, while manual helpdesk data retrieval caused processing delays and strained vendor relationships, and repeated vendor contact for PO confirmations resulted in a high rate of missed confirmations.