We design, modernize, and optimize search systems to improve relevance, performance, and scalability across enterprise, eCommerce, and AI-powered search.
Innovent designs and optimizes distributed search architectures, addressing relevance, performance, and scalability challenges to ensure consistent and reliable search systems.
FindTuner works with Elasticsearch, OpenSearch, and Solr to enhance search performance through intelligence, insights, and control. It enables teams to understand search behavior, apply targeted optimizations, and continuously refine relevance and ranking as data, user behavior, and business strategies evolve.
AI agents use retrieved information to guide decisions and actions. This article explores how search architecture provides authorized, current, and relevant evidence throughout a workflow, while managing the latency and cost of repeated retrieval.
This article explores a practical use of LLMs in search relevance work: identifying poorly performing queries for human review. It describes the evaluation pipeline and compares results from a cross-encoder and a generative model using sample ecommerce searches.
Category Routed Aliases can displace the Gateway Anchor Collection as they create collections and change alias ordering. A CRA-native anchor and ZooKeeper reconciliation preserve distributed query coordination as the alias evolves.
Work with our team to solve relevance, performance, and scalability challenges and design a search platform that performs at scale.
