Case Study: Shelf Engine achieves 15%+ gross margin expansion and reduced food waste with Arize AI

Shelf Engine’s CEO On Disruptive Innovation Without Disruptive Adoption and the AI-Driven Future of Grocery Retail

Shelf Engine, led by CEO Stefan Kalb, is a results-as-a-service company using AI to predict demand and automate ordering for grocers with the goal of eliminating food waste. Faced with hundreds of production edge cases and a large fleet of models running across stores, Shelf Engine needed robust model monitoring and observability; last year they partnered with Arize AI to monitor and observe their ML models (Arize AI’s model monitoring and ML observability capabilities).

Arize AI delivered pre-built error metrics, model lineage/versioning, dashboards and alerts that let Shelf Engine track over 1 million predictions per week across more than 2,000 stores, catch drift proactively, and quickly compare model performance. That visibility and speed have supported Shelf Engine’s business impact — helping divert over 4.5 million pounds of food waste and driving average gross margin dollar expansion of more than 15% — while enabling the company to scale its AI-driven ordering service.

Shelf Engine

Stefan Kalb

Chief Executive Officer