Services
Search and AI services for production systems.
Two practices under one roof. Thirteen years of deep Elasticsearch work: architecture, migration, cluster operations, performance tuning and custom search APIs. Plus an AI search practice for semantic search, cited answers, LLM integration and SmartSearch AI.
- years of Elasticsearch
- 13+
- Elasticsearch projects
- 40+
- node clusters operated
- 200+
- in license savings
- $700k
Elasticsearch services.
Search systems for streaming platforms, e-commerce, retail and enterprise content. From 200+ node clusters handling terabytes a day to patented Core Search APIs with relevance GUIs. The work is operational, not theoretical.
- 01
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.
- 02
Cluster Migration
Endeca → Elasticsearch. On-prem → cloud. Elasticsearch ↔ OpenSearch. License-shopping with full cost modeling. Includes data reindex strategy and zero-downtime cutover plans.
- 03
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.
- 04
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.
- 05
Cluster Health Check
A short structured engagement. Architecture review, configuration audit, performance bottleneck identification, monitoring recommendations, prioritized fix list with effort estimates.
- 06
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.
AI search services.
Modern search is more than a query box. People expect answers they can check, recommendations that learn, and assistants that never show them documents they shouldn't see. We build that for production, from model selection to running systems.
- 01
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.
- 02
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.
- 03
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.
- 04
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.
- 05
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.
- 06
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.
SmartSearch AI vs. Elastic native.
Elastic ships a great search engine. SmartSearch AI adds what teams otherwise build themselves: guided setup and tuning, cited answers, permissions and connectors, installed and tuned by the people who built it.
SmartSearch 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
- 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.