This is like giving a car factory an always‑on air-traffic controller that watches every step of production in real time, finds bottlenecks and waste, and then suggests the fastest, cheapest way to keep parts and cars moving.
Automotive manufacturers struggle with complex, fragmented production and supply-chain processes that cause delays, excess inventory, rework, and high operating costs. Celonis AI aims to automatically discover process inefficiencies and recommend or trigger fixes, improving throughput and on-time delivery while reducing waste.
Proprietary event and process data from customer ERP/MES systems, combined with a specialized process-mining engine embedded into operational workflows, creates strong switching costs and continuous model improvement tied to each manufacturer’s real processes.
Hybrid
Structured SQL
High (Custom Models/Infra)
Real-time ingestion and processing of high-volume event data from ERP, MES, and shop-floor systems; integration into many heterogeneous factory IT environments.
Early Majority
Unlike generic AI analytics, this is tailored to process mining and execution in complex manufacturing and automotive supply chains, focusing on end-to-end process visibility and automation rather than just dashboards.