Turning warehouse management into a SaaS business using AWS with Schreiber

Many of the world’s most recognized food brands rely on Schreiber for consistent supply chain management across its dairy-product manufacturing plants and distribution centers. For years, the company used an internally created tool, called The Hive, for warehouse quality and inventory management. The system managed raw-material receipts; production batches and recipes; quality holds; pallet-level inventory; and outbound picking, packing, and shipping.

Employees regularly used and consistently praised The Hive, and Schreiber saw an opportunity to market the technology to other food manufacturers. “What if this humble dairy manufacturer could become a technology company?” says SriRaj Kantamneni, executive vice president and chief information and digital officer at Schreiber.

However, The Hive ran on the company’s legacy architecture in a single on-premises data center, limiting the solution’s scalability, ability to integrate with diverse enterprise resource planning systems, and DR capabilities for company-wide operations. To modernize and commercialize The Hive, Schreiber needed to retool the system for a cloud architecture.

When the future vision for The Hive took shape, Schreiber turned to AWS, which has successfully migrated over 1.5 million databases. The teams wrote a press release to describe the project’s envisioned end state, and then worked backward to plan the staged migration, which ultimately took 2.5 years. The modernization occurred in stages, starting with rearchitecting and redeploying the user-facing mobile and terminal screens that plant operators use every day, without disrupting live production. Schreiber then rebuilt the backend database and the integration layer that connects The Hive to the company’s other enterprise systems.

The Hive uses Amazon Elastic Container Service (Amazon ECS), a fully managed container orchestration service, on AWS Fargate, a serverless, pay-as-you-go compute engine. For the database layer, Schreiber performed a lift and shift to migrate its legacy database to Amazon Relational Database Service (Amazon RDS) for Oracle to manage time-consuming database administration tasks. This service spans multiple Availability Zones for Oracle deployment and serves as the company’s system of record.

The Hive manages access to its backend services by using Amazon API Gateway—a service for creating, maintaining, and securing APIs at scale. The company also built an internal chat-based assistant on Amazon Bedrock—a solution for building generative AI applications—to answer employees’ plain language questions about standard operating procedures.

AWS ran numerous hands-on workshops at Schreiber’s Green Bay headquarters so that the company’s technologists could break the migration into manageable components and build the skills to do it themselves. “The AWS team invested the time and talent needed to help our colleagues get up to speed on how this journey was going to take place,” says Kantamneni. “That’s a noticeable difference between AWS and the competitive set.”

The Hive now delivers new features about four times faster than it could 1 year earlier, and the company will continue to shorten feature development cycles. The solution runs across multiple Availability Zones and can isolate regional issues. So far, Schreiber has replicated 553 virtual machines to AWS, improving reliability and DR.

The company lowered its total cost of ownership, with the modernized solution requiring less maintenance effort than the legacy system. Schreiber also completed a European migration of The Hive with zero postlaunch issues, making it possible for the company’s European operations to run separately from US ones. Across 14 active warehouse organizations, the European system processes around 160,000 warehouse inventory transactions on a typical weekday—about 4 million per month.

Schreiber has turned The Hive into a commercial SaaS product, generating seven-figure annual recurring revenue that is expected to double next year. External customers have reported more orders delivered on time in full and better workforce management after adopting the solution.

Along with growing The Hive’s customer base, Schreiber is developing agentic AI workflows by using Amazon Bedrock to reduce manual intervention in The Hive transactions while retaining human oversight. “It has been a multiyear journey working alongside AWS, and we’re pretty proud of where we’ve gotten,” says Kantamneni.