Stockorlo is built by operators and engineers with direct experience in e-commerce operations, logistics data infrastructure, demand forecasting product, and applied mathematics.
CEO & Co-Founder
Yuki spent seven years in retail supply chain and e-commerce operations before co-founding Stockorlo. She worked in retail supply planning at Zulily and Redfin, then moved into consulting where she spent time embedded inside mid-market operators diagnosing replenishment failures firsthand. The $140,000 stockout she watched happen at a Seattle outdoor gear retailer in 2022 — while the buying team’s spreadsheet process was still running — is the direct reason Stockorlo exists. She holds an MBA from the University of Washington Foster School of Business.
CTO & Co-Founder
Brennan spent five years at a Seattle-based logistics software company building the data pipelines that powered carrier matching and load visibility across hundreds of thousands of shipments. He understands what it takes to build reliable data infrastructure in logistics environments where the source data is messy, the schemas shift without notice, and the downstream decisions are time-sensitive. At Stockorlo he leads everything from API integrations with Shopify and NetSuite through to the nightly model execution pipeline. He is based in Seattle.
Head of Product
Petra spent three years at Inventory Planner as a product manager, working directly with Shopify merchants to build and improve their demand forecasting and replenishment tools. She knows how mid-market buying teams actually use forecasting software — what they trust, what they ignore, and where well-intentioned product decisions create more work instead of less. At Stockorlo she shapes the operator experience from first sync through daily replenishment review, with a focus on making the right recommendation visible without requiring the operator to interpret a complex model output.
Head of Data Science
Callum completed his Applied Math PhD at the University of Washington with research focused on demand forecasting under intermittent and highly seasonal demand patterns — exactly the conditions that break simple exponential smoothing models during promotional peaks and clearance windows. He designed and built the gradient-boosted time-series decomposition model at the core of Stockorlo’s nightly forecast run, along with the promotion-lift modeling layer that adjusts SKU forecasts when sales events are added to the calendar.
If you are running replenishment across Shopify, NetSuite, or Cin7 and want to see if Stockorlo fits your operation, reach out. Yuki and Brennan handle early conversations themselves.