AI pricing and promotions co-pilot powered by synthetic A/B testing
Skuel AI infers customer intent and friction from their shopping journeys so you can identify the most effective price changes and promotions for your products without live experimentation. In real time. And at scale.
Increase gross margins by 5-15% via prices and promotions that most effectively drive conversion
Live pricing and promotion experiments can damage customer perception, are costly to run, erode margins, and often produce unreliable lift estimates.
Skuel’s Simference™ Engine leverages customer simulation to provide a near-instant, AI-powered yet data-grounded market signal of responses to price changes and promotions without live experimentation.
Skuel addresses a critical gap in pricing and promo analytics
Pricing and Promotions are the biggest drivers of conversion.
Yet, they rely on stale and confounded historical data that does not reflect the needs and wants of the customer right now.
Skuel enables retailers to leverage live market signals to choose the most effective prices and promotions without the risk and cost of live experimentation.
We don’t need big data
Works for Retailers of Any Size
Skuel’s Simference™ Engine is designed to adapt across the retail spectrum regardless of size. By combining foundation model adaptation with decades of consumer behavior science, the system learns accurate counterfactuals even when traffic volumes are modest.
Designed for Practical Deployment
Privacy-First, Cost-Controlled Simulation
Skuel builds counterfactual customer simulations directly from web shopping behavior, without relying on sensitive demographic data. By learning from how customers engage, the platform preserves privacy while capturing the signals that matter most for retail decisions.
To keep costs low without sacrificing fidelity, we fine-tune your own custom Large Language Model whose simulations continuously gets more accurate with use.
Privacy by design. Simulation on your terms.
About us
Vijay Kamble — CEO
Vijay Kamble is an Associate Professor of Business Analytics at the University of Illinois Chicago whose research focuses on applying reinforcement learning and causal inference methods to optimize retail and e-commerce systems. He previously spent a year as a visiting scholar in Amazon’s Pricing and Promotions organization, where he redesigned promotion sourcing algorithms for large-scale sales events such as Prime Day. At Amazon, he saw firsthand how counterfactual evaluation based on observational data is a central challenge in promotions analytics. He co-founded Skuel with Varun when their research showed that AI synthetic data can effectively address this challenge.
Education: PhD in Computer Science, University of California, Berkeley; Postdoc at Stanford.
Formerly at Amazon, Technicolor, and Livsyt.
Varun Gupta — CTO
Varun Gupta is a Professor of Operations and Information Systems at the University of Utah, and an expert in optimization and machine learning for large-scale e-commerce platforms and digital marketplaces. His research focuses on developing algorithms for complex decision systems operating at scale. At Skuel, Varun leads the company’s scientific and technological efforts, advancing the frontier of causal customer simulation from behavioral data.
Education: PhD in Computer Science, Carnegie Mellon University.
Formerly at Microsoft, Google, Bell Labs, University of Chicago Booth School of Business.