
A major oil and gas company needed to optimize supply chain planning, inventory, and logistics amid volatile demand and complex global operations. Vimix deployed a GenAI-augmented supply chain solution that combined forecasting, scenario planning, and natural-language querying so that planners could ask questions in plain language and get actionable insights—reducing stockouts, cutting excess inventory, and improving on-time delivery.
Supply chain planners relied on legacy tools and spreadsheets; getting answers required IT or analyst support. Demand volatility and long lead times made planning difficult. The client wanted a modern, AI-enhanced planning and analytics experience that could scale across regions and categories.
Vimix's GenAI supply chain engagement gave the oil and gas client a modern, AI-augmented planning experience that improved visibility, reduced risk, and enabled faster, data-driven decisions across the supply chain.
We unified demand, inventory, logistics, and supplier data into a modern data platform. We built forecasting and optimization models and exposed them via APIs and a semantic layer.
We developed a natural-language interface so planners could ask questions (e.g. 'Where are we at risk of stockout in the next 30 days?') and receive answers with underlying data and recommended actions. GenAI summarized reports and suggested scenarios.
We integrated the assistant with existing planning and ERP workflows and trained planners on best practices. We iterated based on usage and feedback.
Planners could get answers without waiting for reports or analysts, improving response time to supply and demand changes.
Scenario planning and early warning reduced stockouts and excess inventory, improving service and working capital.
The solution supported expansion to new regions and product lines with consistent methodology and tools.

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Vimix's GenAI supply chain engagement gave the oil and gas client a modern, AI-augmented planning experience that improved visibility, reduced risk, and enabled faster, data-driven decisions across the supply chain.

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