Enercore AI
Enercore AI
Real-time cost-to-serve, demand forecasting, and price optimization
Chemical companies are caught between volatile feedstock costs and fixed contracts — pricing teams lack real-time cost-to-serve visibility and miss demand correlation patterns.
Dynamic cost calculation from feedstock to delivery, updated with live market indices.
XGBoost sales volume prediction with feature importance analysis for pricing decisions.
scipy.optimize profit-maximizing prices balancing margin targets against demand elasticity.
Cortex Search over ~500 market reports for competitive intelligence and trend analysis.
What your data is hiding — patterns invisible to human analysis, detectable only through ML correlation.
Demand for Polypropylene Grade B in Southeast Asia appears random
Demand is ~90% correlated with Crude Oil Brent price with a 3-week lag — enabling predictive inventory positioning
$2M quarterly margin opportunity from lagged correlation insight
Built on Snowflake with enterprise-grade security, rate limiting, and audit logging.
Request a personalized demo to explore how Chemicals Pricing surfaces hidden patterns in your chemicals data.
AI-powered intelligence for energy, construction, and industrial operations.