In March, Celonis hosted its first AI Lab hackathon of the year in Chicago.. The fast-paced, one-day event brought together leading enterprise teams and Celonis solution experts to transform complex business challenges into working, AI-powered prototypes in just hours π!
By tapping into core Celonis Platform capabilities, including Annotation Builder, Orchestration Engine, Prediction Builder, and Process Copilot,Β participants turned raw process data into production-ready AI solutions π€π‘.
Β High-Impact Enterprise Solutions Built in Chicago
ποΈ Product Lifecycle ManagementΒ Cycle Time Prediction
- Industry: Global Tier 1 Automotive Supplier
- The Challenge: Change requests in product lifecycle management frequently suffer from long cycle times, bottlenecks at feedback checkpoints, and lack of visibility from traditional BI tools.
- The Solution: The team built a machine learning tool to predict expected cycle times and flag change requests likely to get stuck. Paired with a Process Copilot, change managers can proactively intervene and move stalled requests forward before they impact delivery timelines.
π² Source-to-Pay (S2P) Order Risk Assessment Assistant
- Industry: Global Food and Pet Care Company
- The Challenge: Decentralized data across purchase orders, contracts, goods receipts, and invoices creates financial risk and compliance bottlenecks. Manual exception handling leaves critical discrepancies unaddressed.
- The Solution: Using Annotation Builder, the team created a controls application that evaluates transactions end-to-end and assigns dynamic risk scores to exceptions. The framework prioritizes high-impact issues for analysts and is designed to evolve into an autonomous agent that routes tasks automatically.
π Digitizing Paper Workflows in Order-to-Cash (O2C)
- Industry: USG (Building Products Manufacturer)
- The Challenge: Heavy logistics rely heavily on physical weigh tickets and Bills of Lading that are manually entered into spreadsheets, creating data entry errors and scaling bottlenecks.
- The Solution: USG leveraged Large Language Models (LLMs) to build an automated ingestion engine within Celonis. The system scans physical tickets, extracts structured data, maps it directly to the O2C data model, and formats standardized invoicesβrouting low-confidence items to human reviewers for 100% accuracy.
βοΈ Proactive 3-Way Matching
- Industry: Global Materials Science Company
- The Challenge: Mismatches between invoices, purchase orders, and goods receipts lead to delayed vendor payments and costly manual reconciliation.
- The Solution: Built on Prediction Builder and Annotation Builder, the solution identifies potential 3-way match failures before they occur and generates automated recommendations to prevent payment halts.
Β π Intelligent Inventory Planning
- Industry: Commercial Vehicles Manufacturer
- The Challenge: Volatile supply chains and shifting logistics timelines make stock optimization difficult.
- The Solution: Using Prediction Builder and Process Copilot, the team created an intelligent supply chain assistant that helps planners optimize stock levels dynamically as logistics conditions change.
π Ready to see how enterprise AI is reshaping business operations? Read the full original article on the Celonis Blog to explore more insights and upcoming AI Lab events! π
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