# How IskayPet unified corporate knowledge with Amazon Bedrock Managed Knowledge Bases

> **Publication**: aitalky (Independent AI Journalism)
> **Canonical Citation URL**: https://aitalky.vercel.app/news/how-iskaypet-unified-corporate-knowledge-with-amazon-bedrock-managed-knowledge-bases
> **Original Source**: [AWS ML Blog](https://aws.amazon.com/blogs/machine-learning/how-iskaypet-unified-corporate-knowledge-with-amazon-bedrock-managed-knowledge-bases/)
> **Author**: Daniel Martinez Rubio (undefined)
> **Published Date**: Thursday, October 22, 2026
> **Category**: INDUSTRY
> **Tags**: AI, AWS ML Blog, industry

## Executive Summary
Learn how IskayPet, a leading pet care company in Iberia, built a multilingual corporate knowledge assistant on Amazon Bedrock Managed Knowledge Bases.



## Full Coverage
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

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