When you think of AI success stories, you might picture Silicon Valley startups or cutting‑edge tech firms. But sometimes the most inspiring examples come from the least expected places. This week’s spotlight lands on Bargreen Ellingson, a 65‑year‑old restaurant supply company that quietly embraced a generative‑AI tool and saw dramatic results. If you’ve ever wondered whether AI is practical for a traditional business with limited resources, this story will give you hope. We’ll walk through what the company did, why it worked and what you can learn from their journey.
Meet Bargreen Ellingson and Netstock’s Opportunity Engine
Bargreen Ellingson is a family‑run business that supplies equipment and supplies to restaurants across North America. Like many wholesalers, it relies on tight margins and precise inventory management. In August 2025, the company’s chief innovation officer, Jacob Moody, decided to test Netstock’s Opportunity Engine, a generative‑AI tool that plugs into an existing inventory dashboard. The Opportunity Engine ingests data from the company’s ERP system and generates real‑time recommendations on what to order, how much to stock and when to reorder. Netstock says it has delivered one million recommendations to date and that 75 % of its customers have received suggestions worth at least $50,000.
Moody knew his colleagues would be skeptical. “Old family companies don’t trust blind change a lot,” he told TechCrunch. Instead of forcing adoption, he pitched the AI as a tool that warehouse managers could either choose to use or ignore. That choice proved critical; employees felt ownership over the process rather than resentment toward a mandated technology.
How the AI Helped
- Uncovering high‑value actions: The Opportunity Engine spots patterns in sales and stock data that humans miss. One recommendation was valued at $50,000, highlighting just how much money can be tied up in inventory decisions.
- Augmenting staff, not replacing them: Moody emphasized that the AI isn’t making decisions on its own. Warehouse managers review every suggestion. By keeping humans in the loop, the company maintains control while benefiting from machine‑generated insights.
- Empowering less‑experienced workers: Some of Bargreen’s staff have only high‑school diplomas. The AI summarizes complex reports so these employees can understand and act on them quickly. This reduces training time and boosts confidence.
- Learning from feedback: The Opportunity Engine uses reinforcement learning; each recommendation can be rated with a thumbs‑up or thumbs‑down and the model adjusts accordingly. The more the team interacts with it, the better its suggestions become.
Lessons for Solopreneurs and Micro‑Businesses
Start With a Small Pilot
Moody didn’t roll out AI company‑wide. He introduced it gradually, giving managers time to test and trust the system. For solopreneurs, the takeaway is to experiment with AI on a limited scale. Try an AI tool on one part of your workflow before integrating it everywhere.
Frame AI as a Co‑Pilot
One reason this story is powerful is that the AI complements human expertise instead of replacing it. The managers still make the final call, and they appreciate the time savings. When you adopt AI in your own business, present it as a helpful assistant rather than a threat to your role or your team’s job security.
Choose Tools That Fit Into Existing Platforms
Netstock’s Opportunity Engine lives inside a dashboard the team already uses. Employees don’t have to learn a new application – they just see new suggestions appear in familiar territory. If you’re considering AI, look for integrations with software you already trust. This reduces onboarding friction and increases the chances your team will embrace the change.
Iterate and Provide Feedback
The engine’s thumbs‑up/thumbs‑down system means users directly influence the model. Similarly, many AI tools allow you to rate or edit outputs. Don’t be passive; actively rate recommendations and correct inaccuracies. Over time, your feedback will improve the model’s relevance to your specific business needs.
Actionable Steps to Replicate Bargreen Ellingson’s Success
- Assess your bottlenecks: Identify areas where you rely on gut instinct or outdated reports. Inventory, pricing and customer service are common pain points for small businesses.
- Research AI partners: Tools like Netstock’s Opportunity Engine are designed for supply‑chain and retail businesses. If you’re in another industry, look for sector‑specific AI solutions.
- Engage your team: Involve staff in the decision to adopt AI. Explain the benefits and give them a chance to experiment. Their buy‑in will determine success.
- Review and iterate: Monitor the recommendations. Approve or reject them consciously so the model learns. Track how much time or money the AI saves you.
- Scale responsibly: Once you see results from a pilot, expand AI usage gradually. Always keep a human in the loop, especially for high‑stakes decisions.
Tradition Meets Technology
Bargreen Ellingson’s story proves that you don’t need to be a tech giant to benefit from AI. By starting small, keeping humans in control and choosing the right tool, the company turned a potential risk into a competitive advantage. As generative AI becomes embedded in mainstream applications, solopreneurs and micro‑businesses have a golden opportunity to modernize operations without losing their personal touch. Take inspiration from this 65‑year‑old success story and consider how a thoughtfully implemented AI assistant could make your business more efficient, resilient and empowered.
