CASE STUDY
Annual savings from efficiency gains in procurement and warehousing
Improvement in delivery performance across B2B accounts
Increase in demand prediction precision across categories
Inventory repositioned based on predictive demand signals
A national wholesale distributor was grappling with outdated forecasting models, siloed inventory data, and slow decision cycles. With over 10,000 SKUs across 14 regional warehouses, they faced constant stockouts in high-demand zones while overstocking slow movers. This led to missed sales, increased carrying costs, and unhappy customers. Despite a robust ERP, decision-makers lacked real-time clarity into what was driving inventory and order issues—and couldn’t act fast enough to correct course.
We designed a decision intelligence layer that unified sales, inventory, and logistics data into a single, interactive command center. AI agents continuously modeled demand, flagged anomalies, and simulated supply chain scenarios—enabling planners to adjust forecasts and reorder points dynamically. With predictive insights surfaced through intuitive dashboards, teams were empowered to act fast, minimize risk, and rebalance stock in real time—transforming inventory into a strategic growth lever.
We gave SaaS teams a real-time brain—syncing product, support, and revenue signals to turn roadmap chaos into high-velocity, data-led execution.
In logistics, we turned routes into real-time revenue plays—connecting data across fleets to spot margin leaks, price dynamically, and move smarter at scale.
In energy ops, we flipped the script on downtime—using AI to predict faults, dispatch faster, and turn every outage into a smarter, faster recovery.