Ten industry personas reach a decision

Manufacturing — defect & yield optimization

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.

• →Automated defect tracking
• →Shorter setup for new processes
• →In-house data only, no external LLM

Hospital — operations & diagnostic assist

Identify operational bottlenecks from bed, staffing, and exam data. XAI-based diagnostic assist satisfies EU AI Act and Korea's AI Framework simultaneously.

• →Shorter patient wait times
• →Optimized staffing
• →Regulator-ready explainable AI

Public Sector — policy scenario simulation

Unify administrative, demographic, and budget data. Reverse What-If derives the policy variables needed to hit a goal (unemployment, birth rate, etc.).

• →NIPA SaaS-program eligible
• →Fast PoC → production
• →Auto-generated policy justification reports

Smart City — urban simulation

Integrated analysis across IoT, traffic, and energy data. Simulate optimal allocation of city resources. Extensible as an AI-agent backend.

• →City KPI visibility
• →Compare traffic and energy scenarios
• →Future agent-integration option

Finance — credit & fraud decisions

SHAP-based per-variable contribution is attached to every credit and fraud score, ready for regulator explainability requests.

• →Adverse-action reasons (regulator-ready)
• →Better fraud accuracy with fewer false positives
• →Air-gapped internal-network deployment

Retail — pricing & inventory optimization

SKU-level price elasticity and inventory turnover regression. Reverse What-If derives the price/promotion mix needed to hit a revenue target.

• →Pre-simulate the impact of price changes
• →Improve inventory turn and stock-out rates
• →Forecast promotion ROI before launch

Logistics — delivery & inventory optimization

Unified analysis of orders, inventory, and fleet positions. Reverse-solve lead-time and cost targets to pick hubs and routes.

• →Shorter delivery lead time
• →Lower freight cost
• →Less stock-out and overstock at the same time

Energy — demand forecast & grid stability

Hourly regression across load, generation, and weather. Reverse What-If outputs the resource mix needed to avoid peak loads.

• →Preempt peak-load events
• →Absorb renewable-output variability
• →Auto-generated justifications for energy-trading

Education — outcome & dropout prediction

Regression across study activity, assessments, and environment. Reverse-solve the study pattern needed to hit a target pass rate.

• →Early dropout signal detection
• →Scenarios to hit a pass-rate target
• →Explainable rationale for parents and learners

Telecom — churn prediction & QoS

Subscriber usage logs, call drops, and plan data. SHAP identifies the variables driving churn risk.

• →Proactive care for high-risk subscribers
• →Identify network quality degradation causes
• →Simulate the impact of new plans

Insurance agency — lead conversion & advisor attrition

Branch lead funnel and advisor activity analysed on-premise. Post-hoc fields are flagged as leakage so apparent high performance is filtered out.

• →Surface the drivers of consultation requests
• →Identify advisors needing early support
• →Pre-empt 13th-month lapse and commission clawback