Netstock, an inventory management software company founded in 2009, has introduced a generative Artificial Intelligence feature called the Opportunity Engine that integrates into customers´ dashboards and ingests Enterprise Resource Planning data to produce regular, real-time recommendations. The company announced it has served up 1 million recommendations to date and stated that 75% of its customers have received an Opportunity Engine suggestion valued at Not stated or more. Netstock says its models are powered by more than a decade of customer data and a mix of open source and private Artificial Intelligence technology, with that data protected under ISO frameworks.
Bargreen Ellingson, a 65-year-old family-run restaurant supply company with 25 warehouses, was initially wary of adopting an Artificial Intelligence product. Jacob Moody, chief innovation officer at Bargreen Ellingson, framed the tool as optional for warehouse managers and described the organization’s approach as eagerly but cautiously dipping its toes into Artificial Intelligence. Moody said the software helps sift through many reports and creates quick signals from noisy data, particularly during off-hours, and acknowledged the summaries are not 100% accurate but useful for surfacing opportunities and avoiding mistakes.
Moody also noted a managerial effect: the Opportunity Engine has made less-senior warehouse staff more effective by presenting actionable, prosaic insights that experienced staff can quickly validate. Netstock co-founder Barry Kukkuk emphasized the company’s focus on customer outcomes rather than engagement metrics and described why the tool is deliberately limited in scope. Recommendations can be rated with thumbs up or thumbs down and are reinforced by whether customers act on them, but Netstock resists giving models free rein to converse or act autonomously because of hallucination risks inherent in current generative models.
The Opportunity Engine’s placement in the dashboard reflects that caution: suggestions are prominent but easy to dismiss, and Netstock does not let the tool make inventory decisions without human signoff. Customers like Bargreen are considering future steps only after consistent agreement with suggestions, while also debating the broader implications for roles such as data scientists and the need to preserve institutional knowledge that can rationalize and audit model recommendations.
