Profinity AI helps retailers improve pricing, markdowns, forecasting, inventory performance, and commercial decision-making with enterprise-grade decision intelligence.
Pricing, markdowns, promotions, demand signals, supplier costs, and inventory actions often operate in silos. The result is slower decisions, excess stock, missed sales, and avoidable margin erosion.
Late clearance actions reduce sell-through and increase inventory write-offs.
Teams lack decision support to balance demand, margin, competition, and inventory.
Inaccurate demand signals create stockouts, overstock, and working capital pressure.
Profinity AI converts retail data into recommended actions across pricing, markdowns, inventory, forecasting, and promotion performance.
Identify commercial actions that directly improve gross margin and EBITDA.
Optimize markdown timing and inventory liquidation decisions by category and location.
Give merchants, pricing, supply chain, and leadership one aligned view of profit levers.
Start with one category, business unit, or region. Profinity AI identifies margin leakage, pricing gaps, markdown opportunities, demand signals, and inventory risks — then converts them into action recommendations.
Data discovery, profit leakage map, baseline KPIs, and opportunity sizing.
Modeling, recommendations, business rule alignment, and merchant review cycles.
Measured outcomes, executive dashboard, scale roadmap, and annual engagement proposal.
Profinity AI is founded by Gayatri Pal, an AI and Data Science leader with deep experience across retail, pricing, markdown, forecasting, supply chain, and enterprise transformation.
Her background includes leadership roles across Tesco, Target, Walmart, IBM, and applied AI programs spanning retail intelligence, predictive analytics, reliability, optimization, and responsible AI governance.
Why this founder can solve your problem: built by an operator who understands retail unit economics, not a generic AI vendor.