MSI Surfaces Scales Corvus One™ Across an 8-State Distribution Network

Overview

In a high-volume distribution business handling tens of thousands of slabs, tiles, and pallets across multi-acre warehouses, inventory accuracy directly impacts order fulfillment speed and customer service. When inventory teams rely on manual cycle counts, discrepancies often surface only during order picking, with cascading effects on delivery commitments and customer trust. MSI Surfaces needed a faster, more consistent way to validate reserve storage across its distribution network.

The Challenges

• Fulfillment Speed: Lost or misplaced inventory delayed customer deliveries, causing dissatisfaction, returns, and unmet service expectations across high-volume distribution operations.
• Inefficient Use of Labor: 2 to 4 warehouse associates per facility were dedicated to manual cycle counting and physical inventory audits, running multi-week passes through racks with annual wall-to-wall counts as the catchall.
• Operational Productivity: Labor was often pulled from fulfillment tasks to locate missing material, with inventory accuracy holding at roughly 80% between counts.

The Corvus Solution

MSI Surfaces deployed the Corvus One™ Autonomous Inventory Management System, beginning in Orange, California and scaling across its nationwide distribution network. Corvus One brings Physical AI to building-materials distribution, running in GPS-denied warehouse environments with onboard AI and computer vision. Drones autonomously fly aisles to validate reserve storage positions without operators, beacons, markers, or infrastructure modifications, with sites becoming operational on day one of installation.

Daily missions sync directly with MSI's WMS through the AIMS platform, producing a searchable, time-stamped visual record of every rack location scanned. Approximately 90 percent of identified discrepancies are auto-classified by type, letting the inventory team correct issues from a desk-side dashboard rather than walking the racks. The system also surfaces operational patterns behind misplacement, turning each discrepancy into a continuous-improvement signal rather than just a fix.

The Impact

• Inventory Accuracy Lifted from 80% to 99%: Continuous drone-led validation replaced manual quarterly and annual cycle counts, driving sustained accuracy from a typical 80% baseline to 99% across deployed facilities.
• Physical-Inventory Labor Eliminated: 2 to 4 employees per site previously dedicated to manual physical inventory now run no dedicated PI cycles. Labor reallocated to higher-value picking, replenishment, and operational improvement work, valued at approximately $110,000 annually per facility.
• Approximately $1.25M in Recovered Inventory: Faster discrepancy detection surfaces misplaced and "missing" inventory that would have been lost or written off during legacy quarterly counts, recovering meaningful dollar value year over year.
• 20x Faster Cycle Counting: Multi-week manual passes through racks compressed to autonomous daily flights, with full network coverage every 2 to 3 days.
• Weekly PI Frequency (Previously Annual): Physical inventory cadence shifted from an annual catchall to weekly autonomous validation at each facility, surfacing issues within days instead of months.