Author: Gilbert V Lepadatu

In this post, we walk through the problem space, our architecture on Amazon Bedrock and Amazon OpenSearch Serverless, the evaluation methodology we built on OpenStreetMap ground truth, four experiments that compared embedding models, fusion strategies, captioning, and search methods, and the practical guidance you can apply when building a similar system. You’ll learn which design choices move the needle for geospatial semantic search, including why Amazon Nova Multimodal Embeddings delivered the highest F1 scores across both benchmark queries in our evaluation. The work described here evolved into Vexcel Intelligence, a searchable imagery product.

In this post, we explore how the AWS Generative AI Innovation Center and Quora collaborated to build a unified wrapper API framework that dramatically accelerates the deployment of Amazon Bedrock FMs on Quora’s Poe system. We detail the technical architecture that bridges Poe’s event-driven ServerSentEvents protocol with Amazon Bedrock REST-based APIs, demonstrate how a template-based configuration system reduced deployment time from days to 15 minutes, and share implementation patterns for protocol translation, error handling, and multi-modal capabilities.