# Query Quotient

> Query Quotient is an AI, agents and search consultancy. We design, build and operate AI agents, retrieval-augmented generation (RAG) systems and AI search on Elasticsearch and OpenSearch for teams taking AI into production.

Based in the United States, working with clients worldwide. Elastic Verified MSP, Elastic Technology Partner and AWS OpenSearch Partner. Contact: hello@queryquotient.com.

## Services
- [RAG Implementation](https://queryquotient.com/services/rag-implementation): Applied AI & RAG - Retrieval-augmented generation, evaluation harnesses and LLM integration that turn your documents and databases into accurate, cited answers.
- [AI Agent Development](https://queryquotient.com/services/ai-agent-builder): AI Agents - Tool-using agents and multi-agent workflows built on Claude, GPT and open models - with guardrails, observability and humans in the loop.
- [Elasticsearch Consulting](https://queryquotient.com/services/elasticsearch-consulting): AI Search - Hybrid, semantic and vector search on Elasticsearch and OpenSearch - architected, tuned and operated for relevance, latency and cost.
- [OpenSearch Consulting](https://queryquotient.com/services/opensearch-consulting): AI Search - Hybrid, semantic and vector search on Elasticsearch and OpenSearch - architected, tuned and operated for relevance, latency and cost.

## Case studies
- [AlphaSense](https://queryquotient.com/case-studies/alphasense): 90% faster queries, 99.99% uptime and 3x better relevancy across 100M+ financial documents on Elasticsearch
- [GrabJobs](https://queryquotient.com/case-studies/grabjobs): 10M+ job listings in 12+ languages with 5ms average query time and 40% lower infrastructure cost on OpenSearch
- [Lenskart](https://queryquotient.com/case-studies/lenskart): 300% conversion increase, sub-100ms responses and 60% better relevancy with personalized Elasticsearch search

## Blog
- [Advanced Search Relevancy Techniques with Elasticsearch](https://queryquotient.com/blog/advanced-search-relevancy-techniques): Improve Elasticsearch relevance by boosting fields and signals with function_score, adding search-time synonyms, combining BM25 with vector search, and measuring every change.
- [Elasticsearch to OpenSearch Migration Guide - Part 1: Why Migrate and Pre-Migration Planning](https://queryquotient.com/blog/elasticsearch-opensearch-migration-part-1): Migrate to OpenSearch when Apache 2.0 licensing, cost or vendor neutrality matter more than Elastic-only features. Plan with a compatibility check, a migration method and a rollback plan.
- [10 Elasticsearch Performance Tuning Tips](https://queryquotient.com/blog/elasticsearch-performance-tuning-2025): The biggest Elasticsearch performance wins come from right-sized shards (10-50GB), correct field types, filter context, bulk indexing, and leaving heap auto-sizing on.
- [Elasticsearch Query Performance Optimization: A Complete Guide](https://queryquotient.com/blog/elasticsearch-query-performance-optimization-guide-2025): Speed up Elasticsearch queries by moving non-scoring clauses to filter context, mapping exact-match fields as keyword, returning less data, sizing shards at 10-50GB and profiling slow queries.
- [Elasticsearch Security Best Practices for Enterprise](https://queryquotient.com/blog/elasticsearch-security-best-practices): Secure Elasticsearch by keeping the default security on, using TLS on both layers, least-privilege roles with field and document security, scoped API keys, and audit logging.
- [Mastering Hybrid Search in OpenSearch: The Best of Both Worlds](https://queryquotient.com/blog/mastering-hybrid-search-opensearch-3-3): OpenSearch hybrid search runs a BM25 query and a vector query together, then a search pipeline normalizes and combines their scores (or fuses ranks with RRF) into one ranked list.
- [Unlocking the Power of Search Pipelines in OpenSearch](https://queryquotient.com/blog/unlocking-search-pipelines-opensearch): An OpenSearch search pipeline is a chain of processors that rewrites search requests and transforms results inside OpenSearch, so query logic lives in the cluster instead of your app.
- [Implementing Zero-Downtime Deployments for Elasticsearch](https://queryquotient.com/blog/zero-downtime-elasticsearch-deployments): Upgrade Elasticsearch without downtime with a rolling upgrade: one node at a time, data tiers first and master-eligible nodes last, waiting for green health between nodes.
- [Your AI agent is only as good as its retriever](https://queryquotient.com/blog/agent-only-as-good-as-its-retriever): When an agent gets answers wrong, teams reach for a bigger model. Published benchmarks point somewhere cheaper: the same agent with a better retriever jumped from 55.9% to 70.1% accuracy and searched less doing it.
- [The reliability math of AI agents: why 95% per step is not good enough](https://queryquotient.com/blog/agent-reliability-math): A 20-step agent that gets each step right 95% of the time finishes cleanly only 36% of the time. Here is the arithmetic, what benchmarks show, and the five design levers that actually move reliability.
- [How RAG fails in production: a field guide to eight failure modes](https://queryquotient.com/blog/how-rag-fails-in-production): Most RAG systems that disappoint in production fail in a handful of predictable ways. For each one: the symptom, the metric that catches it, and the fix.
- [Hybrid search scoring, explained: Elasticsearch 9.5 vs OpenSearch 3.9](https://queryquotient.com/blog/hybrid-search-scoring-explained): We ran the same hybrid queries on Elasticsearch 9.5.5 and OpenSearch 3.9.0 with identical data and vectors. Raw scores differ by exactly 2.2x, fused scores match to four decimals, and your page size can change the ranking.

## Optional
- [Engagements and pricing](https://queryquotient.com/pricing): Advisory from $4,999/month, Build from $9,999/month, or a custom Partner engagement
- [About](https://queryquotient.com/about): Who we are and how we work; led by Abhilash B, Chief Everything Officer
- [Elasticsearch vs OpenSearch](https://queryquotient.com/compare/elasticsearch-vs-opensearch): Features, licensing, performance and migration considerations
- [Elasticsearch vs Algolia](https://queryquotient.com/compare/elasticsearch-vs-algolia): Features, pricing, performance and use cases
- [Elasticsearch vs Solr](https://queryquotient.com/compare/elasticsearch-vs-solr): Features, performance and cloud options for Lucene-based search
- [Resources](https://queryquotient.com/resources): Free cost calculator, cluster health check and production checklist