Search and AI services for production-grade systems. Elasticsearch + AI.
Two practices under one roof. Thirteen years of deep Elasticsearch expertise — architecture, migration, cluster operations, performance tuning, custom search APIs. Plus a modern AI search practice built on hybrid retrieval, RAG, semantic search, LLM integration, and the Smart Search Tools AI agentic relevance framework. We help teams ship production search and AI systems that actually work.
Search that works in production. At enterprise scale.
Our Elasticsearch practice has shipped search systems for streaming platforms, e-commerce, retail, and enterprise content systems. From 200+ node clusters handling terabytes per day to patented Core Search APIs with relevance GUIs, the work is operational, not theoretical.
Enterprise Search Architecture
Hybrid retrieval design from scratch or repair of a struggling system. Query analysis, mapping and analyzer review, ranking logic, evaluation suites tied to measurable outcomes.
Cluster Migration
Endeca → Elasticsearch. On-prem → cloud. Elasticsearch ↔ OpenSearch. License-shopping with full cost modeling. Includes data reindex strategy and zero-downtime cutover plans.
Performance & Cost Review
Cluster sizing, shard strategy, query tuning, payload optimization, cache layer design. Track record: 50–60% latency cuts, $500k–$700k in license savings on real engagements.
Custom Search Solutions
Patented Core Search APIs, Relevance GUIs that let business users tune ranking without backend code, .NET Smart Search APIs. Track record: $17M pre-launch sales, 70% conversion lift, 40% relevance gains.
Cluster Health Check
A short structured engagement. Architecture review, configuration audit, performance bottleneck identification, monitoring recommendations, prioritized fix list with effort estimates.
Embedded Search Advisor
A senior search engineer embedded with your team for the duration of a build. Pair with your engineers, write code, run reviews, transfer expertise. Engagements typically 1–6 months.
Retrieval architecture for the AI era.
Modern search isn't just a query box. RAG pipelines need grounded answers with citations. Recommendation engines need LTR. Customer-facing AI needs weak-evidence detection so it doesn't hallucinate. Our AI search practice covers the full retrieval stack — from embedding model selection to agentic relevance frameworks running in production.
SmartSearch AI
Weblink's agentic search framework, installed in your environment as part of a consulting engagement. Aura, a built-in AI search expert, sets up and tunes search in plain language. Permission-aware search and cited answers across your websites, documents and business systems.
AI Search & Answers
Search and chat that answer from your own content, cite their sources, and say so when the evidence is not there. Built for production, not a demo on a vector database.
Semantic Search Implementation
Vector search architecture, embedding model selection (OpenAI, Cohere, open-source), HNSW vs IVF index choice, hybrid ranking strategy. We pick what fits your data and latency budget.
LLM Integration
Context-aware retrieval, agentic flows with tool calling, prompt engineering for production, evaluation harnesses that catch regressions, permission-aware retrieval with synced ACL data.
AI Use Case Development
Industry-specific AI search solutions: e-commerce product discovery, enterprise knowledge bases, customer support copilots, compliance search. From discovery through pilot through production.
AI Performance Optimization
HNSW tuning (M, efConstruction, ef), embedding caching strategy, payload reduction for vector responses, latency budgeting across the retrieval pipeline, cost optimization for embedding APIs.
What the framework gives you that stock Elasticsearch doesn't.
Elastic ships a great search engine. It doesn't ship an opinionated agentic relevance framework. Smart Search Tools AI fills that gap — sitting on top of Elasticsearch or OpenSearch and giving your team a repeatable way to test, tune, and improve retrieval.
Smart Search Tools AI
- Aura: set up and tune search in plain language, with your approval on every change
- Answers that cite their sources, so people can check them
- Permission-aware by default: single sign-on and document-level access
- Smart Connectors for websites, SharePoint, OneDrive, Google Drive, Confluence, S3 and GitHub
- Search engine included, or connect the Elasticsearch or OpenSearch you already run
- Installed in your cloud or on-premises by our team, as part of a consulting engagement. Not a SaaS subscription
- Evaluation test suites delivered with the system, not as an extra
Elastic Native
- No agentic relevance loops out of the box
- No counterfactual query testing
- LTR plugin exists but is not wired into recommendations by default
- ACL syncing is a separate engineering project
- Cloud-only for ESRE features; on-prem capabilities limited
- License costs scale with data and feature tier
- Evaluation tooling is bring-your-own
Two practices. One conversation.
Tell us what's broken in your search or AI pipeline. We'll review your cluster, queries, mappings, embeddings, ranking logic, and evaluation data — then give you a concrete build plan tied to measurable outcomes.