Vector and hybrid search for RAG and agents, low-risk migrations from Elasticsearch, and AWS OpenSearch tuned for relevance, latency and cost. Open source, operated like production.
OpenSearch gives you keyword, vector and analytics in one Apache 2.0-licensed engine. We make it precise enough for AI, fast enough for users and efficient enough for finance.
k-NN vector and hybrid search that gives RAG systems and agents the right context.
Elasticsearch-to-OpenSearch moves planned for zero downtime, with a tested rollback path.
Amazon OpenSearch Service configured for availability, security and your wider AWS stack.
Right-sized domains, tuned shards and lifecycle policies so you pay for what you use.
Domain sizing, security and networking, monitoring and integration with the rest of your AWS infrastructure - so the managed service stays fast and affordable as you grow.
The search layer behind assistants and agents that must answer from your data.
Matching and ranking across millions of listings, in multiple languages.
Fast, relevant search for e-commerce, content and SaaS products.
Real-time detection and audit trails over security events.
Logs, metrics and traces in one place with sensible retention.
Aggregations and dashboards that turn raw events into decisions.
Assess your cluster or Elasticsearch estate and agree on relevance, latency and cost targets.
Prove hybrid retrieval, migration path or new sizing against your real workload.
Cut over or roll out safely with benchmarks, security review and monitoring.
Continuous tuning and cost control - or a clean handover with runbooks and training.
OpenSearch is an Apache 2.0-licensed search and analytics engine that began as a fork of Elasticsearch. Since 2024 it has been governed by the OpenSearch Software Foundation under the Linux Foundation, and it is available as a managed service on AWS. The two share roots but have diverged in features, plugins and APIs, so the right choice depends on your requirements.
Yes. OpenSearch supports k-NN vector search and hybrid search, so it can serve as the retrieval layer for RAG systems and agent tools - often on infrastructure you already run, without adding a separate vector database.
It depends on your priorities: licensing preferences, AWS integration, feature needs and total cost. We run a migration assessment that compares both options against your workload before you commit either way.
Timelines depend on data volume, cluster complexity and downtime tolerance. Simple migrations can complete in days; complex production migrations typically take 2-6 weeks. We plan for zero-downtime cutover with a tested rollback path.
Yes. We right-size instances and storage, tune index and shard configuration, and implement data lifecycle policies. For GrabJobs, this kind of optimization delivered a 40% infrastructure cost reduction - see the case study for details.
Yes. We offer ongoing retainers covering monitoring, performance and relevance tuning, security management and troubleshooting for both self-managed OpenSearch and Amazon OpenSearch Service.
Planning a migration, an AI search build or a cost review? In a free 30-minute call we will review where you are, what it would take, and how we would measure success.
