Scott Pearson, Vice President of Sales & Marketing

FarsightIQ addresses that gap and helps retailers anticipate demand and position merchandise around customers. Its AI-powered demand engine, ForecastIQ, studies historical sales, product attributes, store locations, channels, and seasonality to produce forecasts that show potential demand when inventory is fully available and realistic demand under current inventory constraints.

“Getting the right products in the right place at the right time still matters — but only if we understand where that demand is coming from,” says Scott Pearson, vice president of sales and marketing. “That’s customer-centric allocation and replenishment, not product-focused planning alone.”

That distinction gives retailers a clearer view of lost opportunities caused by stockouts, and a stronger basis for purchase and allocation decisions. The forecast then turns to retail operations, where ReplenishIQ and OptimizeIQ help determine when merchandise needs to be replenished or transferred. RiskIQ adds another layer by identifying products at risk of overstock, understock, or missed demand. The objective is to place inventory where demand is most likely to emerge while reducing excess inventory, unnecessary transfers, markdowns, and lost sales.

Getting the right products in the right place at the right time still matters — but only if we understand where that demand is coming from. That’s customer-centric allocation and replenishment, not product-focused planning alone.

FarsightIQ’s StyleIQ uses product attributes to find similarities among merchandise and create useful demand signals for items that have never sold before. The intelligence is strengthened further through external data, allowing forecasts to adapt to changing conditions such as weather patterns, social trends, holidays, and local events that can reshape customer demand.

The system also recognizes that every retailer has different priorities. Some may need stronger forecasts for seasonal merchandise, while others may first need visibility into inventory risk or channel differences. FarsightIQ works from those business needs and builds its capabilities around the areas where better decisions can create the greatest value.

Human Judgment at the Center

Data can guide a decision, but retail expertise still matters. FarsightIQ keeps a human in the loop throughout the process, so planners and buyers can review forecasts, adjust them when they possess information the model cannot see, and approve recommendations before execution. The platform can generate a purchase order or suggest a transfer, with the retailer retaining control over the final action.

That approach also fits the technology into current workflows. FarsightIQ can draw data from a retailer’s ERP and other sources, create a common analytical foundation, and feed recommendations back into the systems employees already use. Weekly model updates compare forecasts with actual results and help refine future recommendations to create a continuous cycle of prediction, review, action, and improvement.

FarsightIQ can also identify customer personas, determine where those groups are concentrated, and connect their preferences with products that suit them. That combination of customer intelligence and supply-chain management has earned FarsightIQ recognition as one of the Top AI Powered Predictive Analytics and Machine Learning Solutions in Canada 2026.

The company’s ambition is not to become another system competing for space in the retail technology stack. Instead, it aims to serve as a North Star, helping retailers navigate complexity, anticipate demand and make more confident decisions. As AI evolves from a support function into an active intelligence layer, the retailers that thrive will be those that can translate data into direction. FarsightIQ’s vision reflects that future: a retail ecosystem where technology does not simply report what happened, but helps leaders understand what comes next.