CASE STUDY
Error rates dropped from 1 in 12 to 1 in 25
Efficiency gains from scrap reduction & downtime.
From minutes to seconds on core queries.
IoT-tagged SKUs enabled full traceability.
A global manufacturer of precision components was struggling with outdated data infrastructure that couldn’t keep pace with the demands of its smart factory initiatives. Spreadsheets, disconnected ERP instances, and legacy SQL servers made it nearly impossible to get a real-time view of operations. Teams lacked trust in reports, data silos slowed analytics, and downtime analytics were reactive instead of preventative—costing time, money, and competitive edge.
We rebuilt their data foundation—consolidating fragmented sources into a modern, governed data lakehouse architecture. AI agents mapped relationships across ERP, MES, and sensor systems, while consultants standardized SKUs, hierarchies, and governance protocols. Real-time data pipelines now power a single source of operational truth, enabling predictive maintenance, scrap reduction, and agile inventory control. What was once reactive is now real-time—supporting smarter decisions from the floor to the boardroom.
We rewired the digital grid—turning fragmented feeds into a single current of intelligence that keeps energy flowing, costs falling, and carbon targets within reach.
We turned disjointed hotel data into a unified command center—connecting bookings, loyalty, and spend to forecast demand and personalize every stay.
We re-engineered pharma’s data DNA—connecting trials, labs, and markets into one trusted stream that moves insights faster from molecule to milestone