IskayPet builds multilingual corporate assistant on Amazon Bedrock
IskayPet, a pet care company operating more than 330 stores across Spain, Portugal and France, built a corporate knowledge assistant on Amazon Bedrock Managed Knowledge Bases, according to an AWS Machine Learning Blog case study. The assistant answers employee questions about retail operations, veterinary care, people and onboarding, and procurement in four languages across three countries, using a native SharePoint connector rather than migrating hundreds of existing documents. AWS says the team built the store-facing frontend and the AWS architecture and deployment with Kiro running Claude Haiku 4.5, and that in roughly the first two months in production, time to find an operational answer fell from 3–5 minutes to about 7 seconds, with around 95 percent less time spent searching; the solution is expected to handle roughly 100,000 queries per month.
AWS presents the deployment as an example of using managed RAG to avoid operating vector databases, embedding pipelines and ingestion jobs, while reusing existing SharePoint repositories through a native connector.
IskayPet’s office teams had a knowledge challenge. Answers to everyday operational questions, such as a return policy, a veterinary protocol, or an onboarding step, lived in hundreds of Microsoft SharePoint documents spread across four languages and three countries. Finding the right information in large document repositories took a long time. Every new store, country, or procedure made the problem bigger.
Retrieval Augmented Generation (RAG) is the usual way to solve this. But running RAG in production normally means operating vector databases, embedding pipelines, and ingestion jobs yourself.
In this post, we show how IskayPet, a leading pet care company in Iberia, built a corporate knowledge assistant on Amazon Bedrock Managed Knowledge Bases. The assistant answers employee questions across retail operations, veterinary care, people and onboarding, and procurement, in four languages and across three countries, with no RAG infrastructure to manage. The team built the whole solution, from the store-facing frontend to the AWS architecture and deployment, using Kiro with Claude Haiku 4.5. We cover the architecture, the SharePoint integration, the retrieval configuration decisions, and the results in production.
#IskayPet#Amazon Bedrock Managed Knowledge Bases#Amazon Web Services#Microsoft SharePoint#Kiro#Claude Haiku 4.5