01
Feature preparation
Historical plant demand, supplier realization, coal quality, shipment lead time, and contract values are pulled from governed warehouse models.
A machine learning and optimization platform for forecasting demand, modeling coal supply constraints, and recommending allocation plans across PLN EPI operations.
Tools used
Architecture
01
Historical plant demand, supplier realization, coal quality, shipment lead time, and contract values are pulled from governed warehouse models.
02
Demand and operational input forecasts are generated as planning features, then written back for review and downstream optimization.
03
A constrained solver evaluates allocation candidates and produces recommendations based on cost, availability, quality, and fulfillment requirements.
Work showcase

Purpose-built design, engineering, and infrastructure architecture — crafted for clarity, scale, and production reliability.
Related PLN EPI work
Foundation layer
A governed Snowflake warehouse that standardizes raw operational data into bronze, silver, and gold layers for planning, operations, BI, and AI workloads.
Open detailWorkflow layer
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Open detailAccess layer
A natural-language analytics agent connected to governed operational data, allowing users to ask business questions while keeping answers grounded in approved warehouse models.
Open detail