Ep162: Improving Search for Generative AI Developers with DataStax and AWS

AWS and DataStax discuss how quality data powers AI workloads and applications.

DataStax built on Apache Cassandra powers Starbucks, Netflix, and Uber at scale.

Their TIL app collects outside-in customer feedback to drive product development decisions.

Hybrid search and BM25 kept trending in customer requests for several months.

Customers wanted to go beyond pure vector search, not specifically BM25 itself.

Research showed hybrid search improves accuracy up to 40% over single methods.

ML-based re-rankers substantially outperform score-based ones despite added latency and cost.

DataStax repositioned their product as a knowledge layer above the data layer.

Developer-first design prioritizes simple interfaces and eliminates manual data modeling headaches.

Hybrid search API uses simple dollar-sign parameters and integrates with Langflow automatically.

AWS PrivateLink ensures security while Graviton processors boost efficiency and tenant density.

Graviton reduced total platform operating costs by 20-30% with higher throughput.