Price smarter with data-driven decisions

Transform your pricing strategy with AI-powered optimization that drives revenue growth and increases profit margins at scale.

Smart pricing decisions

Own your pricing process

Set dynamic price adjustments aligned with your business goals. Leverage AI-powered insights from your historical data or run controlled experiments to optimize performance.

Make data-driven decisions

Our AI algorithms analyze multiple factors simultaneously, from seasonality and demand elasticity to competitor strategies and market conditions, ensuring optimal pricing for every item, at every moment.

Optimize inventory management

Seamlessly integrate pricing with inventory control. Predict product demand patterns and automatically adjusts prices to prevent stockout while maximizing margins.

Score your data's readiness for AI pricing

Evaluate your dataset and prepare for smarter Price Optimization

Case study

Dynamic pricing
on two-sided market

For a leading online photography equipment retailer, Tryolabs built an automated pricing system to dynamically adjust buying and selling prices across 60,000 SKUs.

By scraping competitor data and optimizing inventory management, the solution delivered a 10% increase in gross profit while enhancing customer experience through “instant quotes” and transparent pricing.

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10%

increase
in gross profit

Case study

Real-time competitive
pricing optimization

A major Amazon marketplace seller struggled with a semi-automatic pricing system that couldn't keep pace with market changes across 30,000+ products.

The implemented solution now integrates real-time competitor data, sales velocity, and inventory tracking to optimize their top 20,000 products while preventing price wars. A/B testing validated increased profitability and higher Amazon Buy Box wins.

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uplift in profit
in 6 months

Case study

Margin boost with
intelligent pricing

For a brick & mortar luxury retailer with +9,000 employees and 160M customers per year, Tryolabs developed a price optimization solution to replace a traditional pricing process. The client implemented it through weekly changes in the price tags.

Deployment against a control store using the traditional pricing mechanism showed a 28% increase in gross margin for the selected SKUs and significantly reduced out-of-stock related losses.