Financial Intelligence PlatformHow Query Quotient transformed AlphaSense's search infrastructure to handle millions of financial documents with sub-second response times and unprecedented accuracy.
AlphaSense, a leading market intelligence and search platform, was experiencing significant performance bottlenecks as their document corpus grew to over 100 million financial documents. Their existing Elasticsearch infrastructure was struggling with:
Search queries were taking 5-10 seconds for complex financial document searches, impacting user experience and productivity.
New documents were taking hours to become searchable, delaying critical financial intelligence availability.
Users were struggling to find relevant documents due to inadequate relevancy scoring for financial terminology.
Frequent cluster failures during peak usage times were causing service disruptions and data loss concerns.
Query Quotient implemented a comprehensive optimization strategy that addressed each challenge with targeted solutions:
We redesigned the Elasticsearch cluster architecture with:
We developed custom analyzers and scoring algorithms specifically for financial documents:
We built a high-throughput indexing pipeline that ensures documents are searchable within minutes:
The transformation delivered exceptional results that exceeded AlphaSense's expectations:
"Query Quotient's expertise transformed our search capabilities. The 90% improvement in query performance has been a game-changer for our users, allowing them to find critical financial intelligence faster than ever before. Their team's deep understanding of both Elasticsearch and financial data requirements made all the difference."— Sarah Chen, VP of Engineering, AlphaSense
Let's discuss how Query Quotient can help you achieve similar results with your Elasticsearch or OpenSearch implementation.