Case Studies

From concept to launch, here's how we help ideas become impact.

Predictive Maintenance: Manufacturing

Under NDA

AI Chatbot & Customer Analytics

Better Bot

Demand Planning & Inventory Optimization

The North Face

Predictive Maintenance for Manufacturing:
Under NDA

The Challenge

  • Frequent unscheduled downtime due to mechanical failure in production lines.
  • Manual inspections were time-consuming and often reactive.
  • Needed a scalable solution to reduce operational risk.

Data Solution + Value Proposition

  • Developed a machine learning model for predictive maintenance using IoT sensor data.
  • Integrated Azure-based data lake for real-time data collection and model training
  • Enabled root-cause analysis via visual analytics dashboards.

Actual Result + ROI

Reduced equipment downtime by 42% within 6 months.

Saved over $750K in lost production costs annually.

Improved reliability scorecard and maintenance planning accuracy by 60%.

AI Chatbot & Customer Analytics:
Better Bot

The Challenge

  • Chatbot lacked contextual understanding and failed to capture lead conversion trends.
  • No systematic tracking of customer queries, intents, or drop-offs.
  • Stakeholders lacked actionable data to improve bot ROI.

Data Solution + Value Proposition

  • Instrumented event tracking and session analytics for chatbot interactions.
  • Applied NLP classification to group intents and optimize flows.
  • Delivered BI dashboards for engagement, drop-off, and conversion KPIs.

Actual Result + ROI

Boosted chatbot engagement rate by 3.6x through personalized flows.

Increased lead conversion rate by 22% through insight-driven improvements.

Provided executive visibility into $500K worth of marketing- attributed pipeline.

AI-Driven Demand Planning and Inventory Optimization:
The North Face

The Challenge

  • Inconsistent product availability and excess inventory due to demand forecast inaccuracies.
  • Regional buying patterns and seasonality were not fully captured.
  • Lack of predictive insights, limited assortment optimization, and margin protection.

Data Solution + Value Proposition

  • Implemented ML-based demand forecasting models using historical sales, weather, promotions, and regional demographics.
  • Built a centralized inventory visibility dashboard tied to predictive models.
  • Developed product propensity scoring to support assortment decisions at the SKU-store level.

Actual Result + ROI

Improved forecast accuracy by 28% for top seasonal SKUs across key regions.

Reduced excess inventory by $4.2M across 3 key distribution centers.

Increased sell-through rate by 19% through optimized allocation and replenishment.

Empowered merchandising teams with actionable insights into regional product performance and shopper behavior.

LOCATION

  • 107 Corporate Blvd, Suite 876
    Peachtree Corners, GA 30092

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