Value Delivered
GreyB helped the client move from manual inventory planning toward a more predictive, system-driven approach. The client received a structured supplier evaluation framework that clarified which AI inventory management tools could support warehouse automation, demand forecasting, and future SAP readiness.
The findings helped the client reduce selection risk, avoid generic AI claims, and prepare for a controlled pilot without exposing the business to an unsuitable or hard-to-integrate solution.
Problem Solved
The client’s inventory management process relied heavily on spreadsheets and manual tracking. This limited real-time visibility and made the team react to inventory problems after they occurred. Demand fluctuations increased the risk of stockouts, overstocking, and inefficient warehouse planning.
The client needed an AI-based warehouse management solution that could automate inventory decisions, forecast demand, and fit the realities of a chemical warehouse. However, the supplier market was crowded with platforms making similar AI claims. Public information did not clearly show which tools could handle chemical-specific needs such as batch tracking, shelf-life constraints, hazardous material considerations, or SAP integration.
The key challenge was to separate practical, implementation-ready solutions from generic software claims.
Solution Offered
GreyB mapped the client’s operational requirements, including production capacity, product types, warehouse workflows, regional support needs, and upcoming SAP S/4HANA readiness. The team then screened more than 50 global AI and warehouse management solution providers.
Instead of relying only on vendor websites and brochures, GreyB built a weighted scoring framework around the client’s actual needs. The evaluation focused on explainable AI, SAP compatibility, chemical industry fit, implementation readiness, and regional support.
GreyB also carried out direct supplier interactions to verify integration claims, support availability, and deployment feasibility. This helped uncover important differences between tools that appeared similar in public material.
The final output was a confidential shortlist of the most suitable AI inventory management tools, along with a low-risk pilot recommendation for testing the best-fit solution in one warehouse before wider rollout.
Download the full case study to discover how GreyB shortlisted tools to help a chemical company find the right AI Inventory Management Tool.
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