Power generative AI applications with simple, scalable, and high-performing vector store and similarity search
The vector engine for Amazon OpenSearch Serverless introduces a simple, scalable, and high-performing vector storage and search capability that helps developers build machine learning (ML)–augmented search experiences and generative artificial intelligence (AI) applications without having to manage the vector database infrastructure. Get contextually relevant responses across billions of vectors in milliseconds by querying vector embeddings, which can be combined with text-based keywords in a single hybrid request.
Benefits
Increase developer productivity
Colocate your vector and text search to easily query embeddings, metadata, and descriptive text within a single call, increasing search accuracy and reducing system complexity.
Store vector embeddings trained on your business data
Elevate your customer experiences with highly relevant and accurate responses generated by search results based on vector embeddings trained on your business data.
Update vector embeddings in a production-ready search application
Add, update, and delete vector embeddings in near real time without impacting query performance or re-indexing data.
Scalability and efficiency
Store and search billions of vector embeddings with thousands of dimensions in milliseconds with the simplicity of a highly performant and easy-to-use serverless environment.
Use cases
Recommendation engines
Anticipate your customers' needs and provide personalized search experiences geared toward their interests.
Visual search
Improve your decision-making process with object recognition and analysis.
Personalized chatbots
Provide interactive responses and assistance to better support your customers.
Fraud detection
Identify and prevent suspicious activity or transactions through efficient comparisons of similar past fraudulent events.
Customers and partners
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riskCanvas
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Dow Jones
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riskCanvas
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riskCanvas is a subsidiary of Genpact. It is a SaaS product offering for a financial crime compliance solution that uses cutting-edge big data, automation, and machine learning technologies to deliver compliance, efficiency, and automation to its clients.
"riskCanvas directly integrates with the vector engine for Amazon OpenSearch Serverless, allowing us to expose our existing client operational data through AWS’s generative AI capabilities. This is a game changer, as we can now leverage summarization to accelerate the analysis of investigations, author seed narratives of financial crimes reporting, and make recommendations on escalations—all while using real data kept contained within the riskCanvas secure enclave. With the vector engine, we are reducing handle time across financial crimes use cases, improving consistency of narratives with fewer errors, driving higher efficacy via straight-through processing, and shifting human involvement to deeper analysis."
Ryan Skousen, Chief Technology Officer (riskCanvas) and Vice President of Technology, Genpact Financial Crimes
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Dow Jones
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Dow Jones is a global provider of news and information, delivering content to consumers and organizations around the world. It is home to leading publications and products, including the flagship The Wall Street Journal, Barron's, Factiva, Dow Jones Risk & Compliance, Dow Jones Newswires, and Oil Price Information Service (OPIS).
"Observability is critical when developing and managing applications—especially as we adopt more microservices and advanced service mesh-resiliency techniques. We use Amazon OpenSearch Service trace and log analytics to optimize service performance and troubleshoot issues, making our services more reliable and enjoyable to use. Looking to the future, we envision many benefits from using OpenSearch Service. We expect to continue seeing growth and innovation of new capabilities within OpenSearch Service, while looking forward to advancing observability across our product platforms."
Chris Nelligan, Vice President and Fellow of B2B and Platform Engineering, Dow Jones
Resources
The role of vector datastores in generative AI applications
What is a vector database?
Semantic search demo for OpenSearch
Amazon OpenSearch Service’s vector database capabilities explained
Amazon OpenSearch Service for vector search
OpenSearch as a vector database
Product search demo for OpenSearch
