Data ChatGPT can't touch — we work with it daily.
Regression on line data + environmental data identifies defect drivers. Reverse What-If derives the process variables needed to hit a target yield. 100% on-prem.
Identify operational bottlenecks from bed, staffing, and exam data. XAI-based diagnostic assist satisfies EU AI Act and Korea's AI Framework simultaneously.
Unify administrative, demographic, and budget data. Reverse What-If derives the policy variables needed to hit a goal (unemployment, birth rate, etc.).
Integrated analysis across IoT, traffic, and energy data. Simulate optimal allocation of city resources. Extensible as an AI-agent backend.
SHAP-based per-variable contribution is attached to every credit and fraud score, ready for regulator explainability requests.
SKU-level price elasticity and inventory turnover regression. Reverse What-If derives the price/promotion mix needed to hit a revenue target.
Unified analysis of orders, inventory, and fleet positions. Reverse-solve lead-time and cost targets to pick hubs and routes.
Hourly regression across load, generation, and weather. Reverse What-If outputs the resource mix needed to avoid peak loads.
Regression across study activity, assessments, and environment. Reverse-solve the study pattern needed to hit a target pass rate.
Subscriber usage logs, call drops, and plan data. SHAP identifies the variables driving churn risk.
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