Agentic AI for High-Mileage Performance in Margin, Inventory, and Demand.

Protect margins on high-velocity parts and key value items with elasticity-aware pricing tuned to fitment relevance and part criticality.

Move aging inventory profitably with markdown strategies guided by lifecycle stage, part velocity, and model phase-outs.

Respond to regional competitor pricing with zip code–level recommendations that balance margin and market share.

Benchmark pricing across Original Equipment Manufacturer (OEM), aftermarket, and third-party sellers across both online channels and physical retail locations.

Detect similar SKUs even when branded differently using configuration and fitment-aware product matching.

Stay informed with real-time alerts on competitor pricing, service bundles, and promotional activity across national and local players

Predict demand across channels, service zones, and vehicle categories using models trained on fitment logic and historical usage.

Plan for service surges tied to weather, model recalls, and promotional triggers with event-aware forecasting.

Forecast SKU-level slowdowns early to prevent excess inventory in low-velocity categories.

Identify which promotions drive true lift by analyzing historical ROI, regional velocity, and install volume.

Simulate campaign performance ahead of launches to optimize timing, price points, and offer structures.

Time promotions to align with regional weather patterns, travel patterns, seasonal events or manufacturer rebates.

Optimize inventory placement by syncing stock with fitment trends, service demand, and sell-through velocity across distribution centers, retail, and service locations.

Minimize obsolescence for niche or model-specific items by aligning reorders with usage trends and demand signals.

Anticipate demand from recalls, seasonal repairs, and Original Equipment Manufacturer (OEM) incentives with forecasting tuned to part-specific triggers.