Search that works.
At production scale.
Relevance tuning, performance engineering, and search architecture for enterprise Elasticsearch deployments — built by engineers who do this in production every day.
Search engineering across the full stack.
From index design to application-level query performance, we close the gap between “we have Elasticsearch” and “search users actually trust.”
Query optimization and relevance scoring
We tune BM25 scoring, custom field boosting, and function score queries to surface the right results for your users — not just the technically matching ones.
- Query analysis and scoring audit
- Custom relevance tuning for domain-specific data
- A/B testing framework for ranking changes
Index strategy and shard architecture
We design index mappings, shard configurations, and rollover policies that keep your cluster healthy as data volumes grow.
- Mapping design for search performance
- Shard count optimization and rollover strategy
- ILM policy design for data retention
Cluster performance tuning
We identify and fix the heap pressure, merge storms, and slow query patterns that degrade search performance in production environments.
- JVM heap and GC tuning
- Slow query log analysis
- Caching strategy and circuit breaker configuration
Upgrade without the risk.
Elasticsearch major version upgrades and cross-cluster migrations require careful planning. We handle the complexity so your team does not have to.
Major version migrations
We plan and execute upgrades from legacy Elasticsearch versions, handling breaking API changes, mapping incompatibilities, and zero-downtime cutover strategies.
OpenSearch to Elasticsearch
For teams migrating back from OpenSearch or consolidating to the Elastic stack, we handle the data migration, mapping translation, and client library updates.
Let’s fix your search.
Tell us what you are working on. We will respond within one business day with a clear assessment — no sales pitch.