Weblink Technologies designs and repairs enterprise search systems on Elasticsearch, OpenSearch, and Weaviate. We cover hybrid retrieval, RAG, LTR, agentic relevance, and cluster operations for teams that need production-grade results.
Your users see weak results, stale answers, slow queries, and RAG responses without enough evidence. Your engineering team spends time tuning symptoms rather than fixing the retrieval architecture.
Weblink starts at the retrieval layer. We inspect queries, analyzers, mappings, embeddings, ranking logic, source permissions, cluster sizing, and evaluation data, then give your team a build plan tied to measurable search outcomes.
BM25 alone misses semantic intent. Vector alone misses exact terms. Most teams use neither well.
Untuned shard counts, missing caches, and oversized payloads push latency past 1,000ms.
Stale ACL data in the index exposes documents users should not see in search or RAG answers.
Generated answers that cite no source content create compliance risk and user distrust.
Source ingestion through BM25, vector retrieval, hybrid ranking, LTR, RAG answers, citations, and evaluation loops.
Smart Search Tools AI is Weblink's agentic relevance framework for teams that need more than a static search box. It sits on top of Elasticsearch or OpenSearch and gives your team a repeatable way to test, tune, and improve retrieval.
The framework runs three autonomous relevance loops, counterfactual query testing, Loop C for weak-evidence detection, and built-in LTR inside the recommendation engine.
Continuous relevance monitoring against evaluation test suites
Click and engagement signal ingestion for LTR model updates
Weak-evidence detection that triggers counterfactual query paths
Hybrid retrieval, LTR, evaluation, governance.
02BM25 + dense vector + RRF + reranking + RAG with citations.
03Agentic relevance framework with three autonomous loops.
04Endeca → Elasticsearch; on-prem → cloud; ES → OpenSearch.
05Cluster sizing, query tuning, payload optimization, cost reduction.
06Senior search engineer embedded with your team for the duration of the build.
200+ node cluster, $500k+ cost savings, 3x TPS increase
Designed and operated a 200+ node Elasticsearch cluster handling several terabytes per day with sub-400ms response time. Delivered 3x TPS increase and 60% rendering speed gain.
400,000+ daily users, $700k license savings, 50% payload reduction
Built a high-load search system supporting 400,000+ daily users and 5,000 TPS. Delivered $700k in license savings, 60% rendering speed gain, and 50% payload reduction.
Patented Core Search API, 40% relevance gain
Built a patented Core Search API with a Relevance GUI that allows query tuning without backend code changes. Delivered a 40% relevance gain.
$17M pre-launch sales, 70% conversion lift, 85% shorter dev time
Built Smart Search API and ElasticSI in .NET for a visual product search platform. Delivered $17M in pre-launch sales, 70% conversion lift, and 85% shorter development time.
“Weblink's expertise in Elasticsearch allowed us to dramatically improve our content delivery performance while reducing our overall costs. The 99th percentile response times in the final configurations were below 400ms!”
Review queries, mappings, embeddings, cluster, evaluation data. We start with what's actually in production.
Retrieval pipeline blueprint with measurable success criteria. No generic recommendations.
Implement with your team or embed a senior advisor. Code, tests, and evaluation suites shipped together.
Evaluation loops, LTR updates, performance tuning. Continuous improvement, not a one-time deliverable.
Select a query and run the full pipeline. Each stage shows exactly what Smart Search Tools AI executes, from BM25 through Loop C to the final RAG answer.
Simulated run with sample data.
We review your cluster, queries, mappings, ranking logic, and evaluation data, then give you a concrete build plan. No generic audit reports.