Major US Retailer Achieves 6X Faster Time-to-Value with Wallaroo on IBM Power
The Challenge: Bridging the Gap from AI Prototype to Retail Reality
A leading major US retailer faced a common but critical production AI bottleneck: despite a robust pipeline of innovative AI models designed to revolutionize the shopping experience, the path to production was riddled with technical friction. Their data science teams were spending months refactoring code and managing low-level infrastructure, delaying the rollout of critical services like real-time inventory forecasting and personalized customer assistants.
To scale their AI initiatives across thousands of locations and millions of digital touchpoints, the retailer needed a production-grade platform that could maximize their investment in IBM Power servers while simplifying the complex production AI lifecycle.
The Solution: Wallaroo Optimized for IBM Power
The retailer partnered with Wallaroo.AI to unleash its enterprise AI inference platform, specifically optimized for the high-performance architecture of IBM Power. By leveraging Wallaroo’s high-performance inference engine and automated “autopackaging” capabilities, the retailer unified their AI operations.
This powerful combination allowed the retailer to deploy complex models—ranging from Computer Vision for in-store analytics to Large Language Models (LLMs) for virtual assistants—directly onto their existing IBM Power infrastructure with minimal manual intervention.
“The flexibility & performance that Wallaroo enables for deploying AI and running inference on a wide range of models on IBM Power are critical for accelerating and scaling our AI initiatives.”
— Enterprise AI Architect, Major US Retailer
Key Retail Use Cases Supported
By running Wallaroo on IBM Power, the retailer successfully streamlined several mission-critical AI applications:
- Virtual Shopping Assistants:
- Powering natural language interfaces that provide instant, personalized support to online and in-app shoppers.
- Inventory Demand Forecasting:
- Utilizing deep learning models to predict stock requirements with hyper-local precision, reducing waste and out-of-stock incidents.
- Online Product Recommendations:
- Driving revenue through real-time, high-throughput inference that delivers tailored product suggestions based on live user behavior.
The Outcomes: Retail Intelligence at the Speed of Business
The integration of Wallaroo and IBM Power delivered transformative business results, turning AI from an AI model development cost center into a production value driver:
- 4-6X Faster Time-to-Value:
- What previously took 3–4 months to move from development to production now takes an average of 2 weeks. This agility allows the retailer to respond to market shifts and seasonal trends in real-time.
- 80% Infrastructure Overhead Reduction:
- Wallaroo’s efficient memory management and high-performance engine maximized the utilization of IBM Power hardware. By running more models on fewer resources, the retailer drastically lowered their total cost of ownership (TCO).
- 40% Increased Operational Efficiency:
- By automating the packaging, deployment, and monitoring of models, data scientists are now empowered with self-service tools. This has eliminated operational bottlenecks and allowed the team to focus on building better models rather than managing infrastructure.
Conclusion
Through the strategic combination of Wallaroo and IBM Power, this major US retailer has established a future-proof foundation for AI. They are no longer just “doing AI”—they are running it at scale, with the speed and efficiency required to lead in the modern retail landscape.
Ready to scale your AI?
Learn more about how Wallaroo.AI and IBM Power can accelerate your production AI journey at Wallaroo.ai and the Wallaroo AI Starter Kit
