Use Cases

Solving real business problems with intelligent data and AI

Most business challenges don’t exist in isolation…

A missed forecast affects inventory.
Poor data quality slows sales.
Operational inefficiencies inflate costs.
AI initiatives stall because no one trusts the inputs.

These challenges appear in different parts of the business—but they share a common pattern:

Decisions are being made without timely, connected, and actionable insight.

Lux Intelligent Solutions solves this by unifying data, processes, and intelligence into connected systems that deliver timely, trustworthy insight—so decisions can be made with confidence, not guesswork.

This same foundation supports a wide range of use cases:

How We Engage

  • Assess: Identify revenue leakage and data fragmentation

  • Design: Define customer and revenue intelligence models

  • Execute: Deploy dashboards, scoring, and forecasts

  • Enable: Standardize metrics and decision workflows

Representative Use Cases

  • Pipeline health and lead scoring

  • Revenue forecasting and scenario modeling

  • Marketing attribution and ROI analysis

  • Customer segmentation and account prioritization

Typical Problems

  • Inaccurate forecasts

  • Poor pipeline visibility

  • Unclear marketing ROI

  • Fragmented customer data

Move from activity tracking to predictable revenue intelligence.

Sales and Marketing

How We Engage

  • Assess: Diagnose demand, inventory, and planning gaps

  • Design: Build integrated supply chain data and analytics models

  • Execute: Deploy forecasting, dashboards, and alerts

  • Enable: Embed insights into planning workflows

Representative Use Cases

  • Demand forecasting and variability analysis

  • Inventory optimization and risk monitoring

  • Supplier performance and lead-time analytics

  • End-to-end supply chain visibility

Typical Problems

  • Inaccurate forecasts

  • Excess inventory or frequent stock-outs

  • Reactive planning

  • Poor supplier visibility

Align demand, inventory, and execution using connected, predictive intelligence.

Supply Chain & Operations

Manufacturing

Improve yield, quality, and throughput by embedding intelligence directly into manufacturing operations.

Typical Problems

  • Defects discovered too late

  • Manual or inconsistent inspections

  • Slow root cause analysis

  • AI pilots that don’t scale beyond one line or site

How Lux Engage

  • Assess: Identify high-impact quality and inspection opportunities

  • Design: Define data, vision, analytics, and deployment architecture

  • Execute: Deliver inspection pipelines and analytics workflows

  • Enable: Govern model lifecycle and scale across sites

Representative Use Cases

  • Visual inspection and defect intelligence

  • Process monitoring and quality analytics

  • Root cause analysis using image, sensor, and MES data

  • Scalable AI deployment across plants

Customer & Service Operations

Typical Problems

  • Customer Churn identified too late

  • Fragmented service data

  • Inconsistent experience measurement

  • Poor prioritization of service effort

  • Manual Scheduling and operations

Shift from reactive support to proactive customer experience management.

How Lux Engage

  • Assess: Identify churn drivers and service inefficiencies

  • Design: Build unified customer and service intelligence

  • Execute: Deploy analytics, automation, and risk indicators

  • Enable: Embed insights into service operations

Representative Use Cases

  • Customer experience and service analytics

  • Churn and retention risk detection

  • Service Task Automation

  • Customer segmentation and prioritization