Synthetic experimentation for pricing and promotions
Traditional A/B testing flies blind — Skuel AI runs LLM-powered synthetic tests using live customer behavior data so brands can identify the most impactful price changes and promos before running live experiments
Live pricing experiments are best minimized
Live pricing experiments damage customer trust, erode margins, and often produce unreliable lift estimates.
Skuel’s Simference™ Engine simulates customer shopping behavior to predict how customers will respond to offer changes before exposing them to live experiments.
Rich intervention landscape and scarce traffic mean test prioritization is key
Large product catalogs, cross-product substitution behavior, several promotion types, and discount depths create a vast experimentation space that is far too large to explore with live traffic alone.
At the same time, traffic is limited, and conversion rates are low, making it feasible to run only a small fraction of potential experiments with adequate statistical power. As a result, test prioritization is crucial.
Skuel AI helps brands aggressively prioritize the few pricing and promotion ideas most likely to move the needle before exposing customers to risky and costly live experiments.
Skuel AI continually learns from live experiments
Every live experiment strengthens the Skuel Simference™ Engine, improving future synthetic predictions and helping brands rely less on live experimentation over time.
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.