TK Elevator: Moving Beyond with Data + AI Driven Service Intelligence
TK Elevator
TK Elevator (TKE), one of the world's largest providers of elevators, escalators and vertical transportation systems, adopted the Databricks Platform to unify and process more than 500 million IoT telemetry events daily from connected elevators across 30+ countries, moving from reactive to predictive maintenance. TKE's MAX platform generates predictive insights that feed actionable guidance to field technicians via its Digital Operations Center (DOC), which generates 30,000-40,000 tickets annually and has reduced technician troubleshooting time on call-backs and unplanned shutdowns by up to 20%. The platform scaled from 3 to over 40 markets (10x expansion), cut data pipeline delivery from months to weeks, and reduced data sharing time with internal/external consumers from three months to three days (90% reduction). TKE uses Delta Lake, Delta Sharing, Lakeflow, Unity Catalog, Databricks Assistant, MLflow, AI Gateway, Vector Search and Model Serving, and is exploring agentic AI to combine technical, service and commercial context in real time.
Overview
TK Elevator (TKE), one of the world's largest providers of elevators, escalators and vertical transportation systems, adopted the Databricks Platform to unify and process more than 500 million IoT telemetry events daily from connected elevators across 30+ countries, moving from reactive to predictive maintenance. TKE's MAX platform generates predictive insights that feed actionable guidance to field technicians via its Digital Operations Center (DOC), which generates 30,000-40,000 tickets annually and has reduced technician troubleshooting time on call-backs and unplanned shutdowns by up to 20%. The platform scaled from 3 to over 40 markets (10x expansion), cut data pipeline delivery from months to weeks, and reduced data sharing time with internal/external consumers from three months to three days (90% reduction). TKE uses Delta Lake, Delta Sharing, Lakeflow, Unity Catalog, Databricks Assistant, MLflow, AI Gateway, Vector Search and Model Serving, and is exploring agentic AI to combine technical, service and commercial context in real time.
The challenge
TKE wanted to use data and AI for predictive maintenance and AI-assisted diagnostics for field technicians, but fragmented systems and limited access to IoT data made it difficult to scale these initiatives; traditional relational databases were not designed to handle the volume and velocity of continuous telemetry signals, and telemetry needed to be integrated with fragmented enterprise systems and unstructured sources such as manuals, service records and contracts.
The solution
TKE adopted the Databricks Platform to unify and process more than 500 million IoT telemetry events daily from connected elevators across 30+ countries. Delta Lake serves as the core storage architecture with a medallion (bronze/silver/gold) structure; Delta Sharing securely distributes datasets across systems like Salesforce and external partners; Lakeflow orchestrates data pipelines; Unity Catalog provides role-based access control and lineage tracking; Databricks Assistant, MLflow, AI Gateway, Vector Search and Model Serving support AI tooling for predictive models, deployed on Databricks' serverless compute.
Reported business value
TKE's Digital Operations Center generates 30,000-40,000 maintenance tickets annually and has reduced technician troubleshooting time on call-backs and unplanned shutdowns by up to 20%. The platform scaled from 3 to over 40 markets, a more than 10x expansion. Data pipeline delivery moved from months to weeks, and data sharing time with internal/external consumers dropped from three months to three days, a 90% reduction. TKE is exploring how agentic AI can further enhance customer satisfaction, elevator uptime and availability.
Sources
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