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Title
Bynder Reduces Search Time by 75% Using Amazon Bedrock with Amazon Titan Multimodal Embeddings
…very easy to get those vectors because it was a very clear API,” says Bankras. One of Bynder’s customers states that the time spent searching for assets for a typical campaign task has decreased by 75%, resulting in a big boost in productivity for the team. The search results are…
Description
Bynder, a digital asset management company serving over 4,000 companies globally and storing more than 175 million assets (18 PB of data), built visual-similarity search using Amazon Titan Multimodal Embeddings in Amazon Bedrock. The solution converts images and search queries into vectors to match by visual and contextual similarity. One Bynder customer reports that time spent searching for assets for a typical campaign task decreased by 75%, and search results return approximately 50% more relevant options on average. Bynder does not use customer data to train the underlying large language model. The company is now exploring frame-by-frame video indexing.
…rage per search 50% Overview Through its solution for digital asset management, Bynder helps over 4,000 companies globally store, organize, and distribute over 175 million assets, totaling 18 PB of data. For digital asset management users, content findability is of paramount importa…
…roductivity for the team. The search results are also deeper and more accurate, returning approximately 50 percent more options on average. Most importantly, the solution scales effortlessly across customers’ massive as…
Company
Bynder
…ansformed how its customers discover and use their digital assets. About Bynder Founded in 2013, Bynder offers a solution for digital asset management. The company has seven offices around the globe, including those in the Netherla…
Industry
Technology & Software
…ansformed how its customers discover and use their digital assets. About Bynder Founded in 2013, Bynder offers a solution for digital asset management. The company has seven offices around the globe, including those in the Netherla…
Problem
For digital-asset-management users, content findability is critical, and any improvement in the speed and accuracy of search delivers significant value; Bynder, which helps over 4,000 companies globally store, organize and distribute more than 175 million assets totaling 18 PB of data, sought to extend its AI-powered search capabilities to improve how customers discover and use their digital assets.
…tore, organize, and distribute over 175 million assets, totaling 18 PB of data. For digital asset management users, content findability is of paramount importance, and any improvements in the speed and accuracy of search are a significant benefit. As a longtime customer of Amazon Web Services (AWS), Bynder chose to implement…
Solution
Bynder implemented visual-similarity search powered by Amazon Titan Multimodal Embeddings in Amazon Bedrock. The solution converts both images and text search queries into vectors, matching assets by visual and contextual similarity, letting customers find assets by selecting similar images or describing what they're looking for in natural language.
…are a significant benefit. As a longtime customer of Amazon Web Services (AWS), Bynder chose to implement visual-similarity search that is powered by Amazon Titan Multimodal Embedding s in Amazon Bedrock , which provides an easy way to build and scale generative artificial intellige…
…en users input a query, the platform processes it through Amazon Bedrock. Then, both the search terms and the stored images are converted into vectors to identify matches according to visual and contextual similarity. “The setup using Amazon Bedrock made it very easy to get those vectors because…
Business value
One Bynder customer reports that time spent searching for assets for a typical campaign task decreased by 75%, and search results return approximately 50% more relevant options on average. The solution scales effortlessly across customers' massive asset libraries with virtually no limitations on image quantity, and Bynder does not use customer data to train the underlying large language model.
…very easy to get those vectors because it was a very clear API,” says Bankras. One of Bynder’s customers states that the time spent searching for assets for a typical campaign task has decreased by 75%, resulting in a big boost in productivity for the team. The search results are…
…privacy and intellectual property rights of its customers’ digital content, as their data is not used to train the large language model. The company is now exploring ways to analyze and index video content frame by f…
AI capabilities
Recommendation & Personalization
…nder extended its comprehensive AI-powered search capabilities in its software. The solution converts images into vectors using Titan Multimodal Embeddings so that customers can find assets by selecting similar images or describing what they’re looking for in natural language. When users input a query, the platform processes it through Amazon Bedrock. The…
Technology
Amazon Bedrock, Amazon Titan Multimodal Embeddings
…ankras Director of System Architecture, Bynder AWS Services Used Amazon Bedrock Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, DeepSeek, Lu…
Deployment model
Cloud
…ankras Director of System Architecture, Bynder AWS Services Used Amazon Bedrock Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, DeepSeek, Lu…
Deployment options
cloud
…ankras Director of System Architecture, Bynder AWS Services Used Amazon Bedrock Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, DeepSeek, Lu…
Implementation approach
Bynder began testing the newly released Amazon Titan Multimodal Embeddings API at the 2023 AWS re:Invent conference and quickly got it running, building on an earlier acquisition that had brought visual search capabilities into its software; the company is now exploring frame-by-frame video indexing as a next step.
…. The fast rate of customer adoption encouraged Bynder to build on its success. At the 2023 AWS re:Invent conference, Bynder realized that the newly released Amazon Titan Multimodal Embeddings would empower its team to continue to innovate and deliver AI capabilities at an even faster rate. Using the Titan Multimodal…
…tunity | Using Amazon Bedrock to Optimize Multimodal Asset Discovery for Bynder Bynder initially acquired a company to incorporate visual search capabilities into its software. The fast rate of customer adoption encouraged Bynder to build on its success. A…
