Alexa+ Integrations

Amazon's cloud-driven voice assistant, Alexa, is accessible on a vast array of devices, both from Amazon and various third-party manufacturers. This innovative technology enables the creation of seamless voice interactions, allowing users to engage with their everyday technology in a more natural manner. To facilitate development for Alexa, a wide array of resources such as tools, APIs, reference solutions, and comprehensive documentation are available. Begin your journey into voice technology by creating Alexa skills, linking Alexa with devices, or embedding it directly into your offerings. Additionally, you can leverage our Alexa Solution Provider network, which offers an extensive suite of services including strategic guidance, validated reference architectures, hardware solutions, and support for both software development and market entry strategies. The possibilities for enhancing user experiences through voice technology are vast and waiting to be explored.

The Model Context Protocol (MCP) is a flexible, open-source framework that streamlines the interaction between AI models and external data sources. It enables developers to create complex workflows by connecting LLMs with databases, files, and web services, offering a standardized approach for AI applications. MCP’s client-server architecture ensures seamless integration, while its growing list of integrations makes it easy to connect with different LLM providers. The protocol is ideal for those looking to build scalable AI agents with strong data security practices.

Overflow is an AEO platform for brands that sell on major retail marketplaces and want to improve visibility in AI-powered shopping search. The platform monitors how products and brands appear in AI search, AI product recommendations, and marketplace AI assistants across Amazon, Walmart, and Target. Overflow gives each brand an AEO Score that reflects its reach, visibility, and competitive position across retailers. Teams can break performance down by marketplace to see whether they are stronger on Amazon, weaker on Walmart, or missing opportunities on Target. The platform turns the score into prioritized recommendations for improving product content, customer Q&A, listing attributes, and AI-readable messaging. Overflow also helps brands compare against competitors to identify gaps that may be lowering visibility or rankings in AI-driven results. As teams make updates, the platform tracks changes week over week so brands can measure score movement, query coverage, and competitive ground recovered. Its workflow is designed to help brands scan their retailers, apply smart fixes, and treat each listing as part of the algorithm that shapes AI recommendations. Overflow helps ecommerce and retail media teams move beyond traditional listing optimization and optimize specifically for how AI shopping systems understand and recommend products.