Smarter AI-driven recommendations with a new approach to vector search

About this webinar
Traditional recommendation systems often fall short, struggling to deliver accurate and relevant results due to their inability to incorporate semantic search and similarity capabilities at scale. Watch this webinar to learn a new approach to vector search that enables smarter, more precise recommendations for use cases like personalized ad serving and fraud detection. Key benefits of this innovative approach include:
Real-time, fresh results: Self-healing indexing keeps recommendations accurate and up-to-date as your data evolves.
Optimized cost-performance: Flexible storage options, from in-memory to hybrid, scale with your workload and budget.
Simplified integration: Easily incorporate Aerospike Vector Search into your AI stack with LangChain, AWS Bedrock, and more to accelerate deployment.