AI-Powered Search That Understands Intent, Not Keywords

Whether you're optimizing product discovery for customers or knowledge search for employees, we deliver semantic search, vector search, and GenAI-powered relevance on Elasticsearch. 60+ search case studies. Innovation Award 2023. 24-hour response SLA.

E-commerce & Product Search → Knowledge & Document Search →

↓ Explore both tracks below or choose your path now ↓

AI-powered search interface showing semantic understanding and intent recognition for both product and knowledge search

TRACK A: E-COMMERCE

E-commerce & Product Search — Turn Browsers Into Buyers

AI-powered product discovery, personalization, and merchandising optimization on Elasticsearch.

Search Conversion Stalling

Users search but don't buy. Zero-results searches are killing our revenue. Manual relevance tuning takes months to keep up with catalog changes. You're leaving 10-20% conversion on the table.

Product Relevance Optimizer

Personalization Lag

Customers expect Amazon-level relevance. Can't personalize search per user — no browsing history, no purchase patterns, no intent prediction. Competitors are winning on personalization while you're stuck with keyword-only search.

Vector Search + User Embeddings

Merchandising Blind Spots

We can't tell which products are buried in search results. No visibility into what's ranking, what's converting, what's being ignored. Can't A/B test search algorithms or boost high-margin products during campaigns.

Search Analytics Dashboard

Turn Browsers Into Buyers

Product Relevance Optimizer accelerator — semantic search, vector embeddings, and merchandising control for e-commerce catalogs.

Semantic Product Search

Understands user intent beyond keywords. “Red dress” matches “crimson gown”, “burgundy frock”, “scarlet evening wear”. Reduces zero-results pages by 30% using NLP and language models trained on your catalog.

AI-Powered Personalization

Vector embeddings for user behavior, purchase history, browsing patterns. Users who searched for “camping gear” see personalized results for “outdoor equipment”, “trail sneakers”, “hiking backpacks” based on their intent profile. 15% average conversion lift.

Merchandising Control

A/B test search algorithms. Boost/bury products by business rules (margin, inventory, seasonality). Set featured products for campaigns. Track what's ranking, what's converting, what's ignored. Transparent analytics for every search query.

Production-Ready, Not Prototype

Deployed and customized by SquareShift engineers (not self-serve SaaS). Includes proven patterns from 10+ e-commerce search engagements. Reduces deployment from 6 months (custom build) to accelerator deployment. Pre-engineered. Expert-deployed. Custom-fitted.

Fashion Retailer — 15% Conversion Lift

Challenge

Product search conversion stalled at 8%. Users frequently hit zero-results pages. Manual relevance tuning couldn't keep up with 50K+ product catalog changes.

Solution

SquareShift implemented semantic product search + vector embeddings for personalization + A/B testing framework using Product Relevance Optimizer accelerator.

Results

15% conversion lift (8% → 9.2%)
30% reduction in zero-results pages
$500K incremental revenue in first quarter

Read Full Case Study

E-commerce search case study dashboard showing conversion lift, zero-results reduction, and revenue impact metrics

Product Relevance Optimizer Accelerator

Pre-engineered Elasticsearch configuration for e-commerce product catalogs. Includes semantic search setup, vector embeddings for personalization, A/B testing framework, and merchandising dashboard.

Deployed and customized by SquareShift engineers (not self-serve SaaS). Reduces time-to-value from 6 months (custom build) to accelerator deployment.

Pre-engineered. Expert-deployed. Custom-fitted.

Includes proven patterns from 10+ e-commerce search engagements.

Learn More About Product Relevance Optimizer →

Audit My Product Search

Free 1-week assessment. See what 15% conversion lift could mean for your revenue. 24-hour response SLA.

TRACK B: ENTERPRISE

Knowledge & Document Search — Surface Answers, Not Just Documents

AI-powered enterprise search for knowledge bases, legal discovery, employee self-service, and internal wikis on Elasticsearch.

Knowledge Base Fragmentation

Internal knowledge scattered across tickets, docs, FAQs, wikis. Employees can't find what they need. Support tickets for basic questions we've already documented. 200% ticket spike after product launches.

Ticket Knowledge Base

Legal Discovery Bottleneck

Legal discovery takes 8 weeks per case. Manual document search for 100K+ documents. Keyword search misses semantic matches in contracts (“contract termination” doesn't find “agreement cancellation clause”). Can't prove compliance to auditors.

Semantic Document Search

Employee Self-Service Failure

HR knowledge base is hard to search. Employees create support tickets for FAQ-level questions. Agents manually search docs for every ticket. Knowledge base exists but customers/employees can't find answers.

AI Assisted Triage

Surface Answers, Not Just Documents

Ticket Knowledge Base + AI Assisted Triage accelerators — semantic search, RAG, and LLM-powered answer extraction for enterprise knowledge.

Semantic Document Search

Understands meaning beyond keywords. “Contract termination” matches “agreement cancellation clause”, “end of service terms”, “termination provisions”. 40% faster legal discovery using NLP trained on your document corpus. 90% semantic match accuracy vs. 60% keyword-only.

AI-Powered Triage

LLM-powered answer extraction from knowledge base. Automatic ticket routing. Suggested resolutions from existing docs. Deflects 60% of support tickets via AI-suggested answers. Agents focus on complex issues, not repetitive FAQs.

RAG Integration

Retrieval-Augmented Generation for context-aware answers, not just document links. Employees get direct answers from HR policies instead of reading 50-page PDFs. 80% employee self-service rate. Reduces support load by surfacing exact policy clauses, not full documents.