Vector-Powered Semantic Product Search & Visual Re-Ranking Engine

Replace keyword-based search with OpenAI vector embeddings and contextual buyer intent.

System Overview & Capabilities

Next-generation e-commerce search middleware. Generates semantic vector embeddings for product inventories, enabling shoppers to find items using conversational queries, vague visual descriptions, or natural problem statements.

Included Production Specifications

Dense vector search powered by pgvector and OpenAI text-embedding-3-small models

Understands conversational queries (e.g. 'comfortable shoes for wide feet on rainy days')

Hybrid search architecture combining vector similarity with traditional BM25 keyword matching

Real-time analytics portal tracking search zero-results, conversion rates, and revenue per search

Technology Stack & Runtime

Node.jsDockerPostgreSQL

Base Project Scope

$1,000 USD

Fixed price · Milestone delivery · 30-day warranty

Estimated timeline: 2 – 4 Weeks

Full Source Code Handover

Signed Mutual NDA Upfront

Inquire About This Build

Inquiries sent directly to info@xoftsol.com

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