In today's fast-paced, high-tech landscape, the way businesses handle the discovery and utilization of their digital media assets can have a huge impact on their advertising, e-commerce, and content creation. The importance and demand for intelligent and accurate digital media asset searches is essential and has fueled businesses to be more innovative in how those assets are stored and searched, to meet the needs of their customers. Addressing both customers’ needs, and overall business needs of efficient asset search can be met by leveraging cloud computing and the cutting-edge prowess of artificial intelligence (AI) technologies.
Now, let's dive right into a real-life scenario. An asset management company has an extensive library of digital image assets. Currently, their clients have no easy way to search for images based on embedded objects and content in the images. The company’s main objective is to provide an intelligent and accurate retrieval solution which will allow their clients to search based on embedded objects and content. So, to satisfy this objective, we introduce a formidable duo: the vector engine for Amazon OpenSearch Serverless, along with Amazon Rekognition. The combined strengths of Amazon Rekognition and OpenSearch Serverless will provide intelligent and accurate digital image search capabilities that will meet the company’s objective.
The architecture for this intelligent image search system consists of several key components that work together to deliver a smooth and responsive user experience. Let's take a closer look:
- Extracts metadata from images using Amazon Rekognition's `detect_labels` API call.
- Creates vector embeddings for the labels extracted from the image.
- Stores the vector data embeddings into the OpenSearch Vector Search Collection in a serverless manner.
- Labels are identified and marked as tags, which are then assigned to .jpeg formatted images.
The choice to utilize the OpenSearch Vector Search Collection as a vector database for this use case offers significant advantages:
The combined strengths of the vector engine for Amazon OpenSearch Serverless and Amazon Rekognition mark a new era of efficiency, cost-effectiveness, and heightened user satisfaction in intelligent and accurate digital media asset searches. This solution equips businesses with the tools to explore new possibilities, establishing itself as a vital asset for industries reliant on robust image management systems.
The benefits of this solution have been measured in these key areas:
In summary, the fusion of the vector engine for Amazon OpenSearch Serverless and Amazon Rekognition for intelligent and accurate digital image search capabilities has proven to be a game-changer for businesses, especially for businesses seeking to leverage this type of solution to streamline and improve the utilization of their image repository for advertising, e-commerce, and content creation.
If you’re looking to modernize your cloud journey with AWS, and want to learn more about the serverless capabilities of Amazon OpenSearch Service, the vector engine, and other technologies, please contact us.