The Modern Search Stack: Implementing AI-Driven Semantic Search with Elasticsearch and Spring

How To Build a Semantic Search API With Spring Boot & Elasticsearch (Real-World Transactions Use Case)

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Hello guys, traditional keyword-based search is no longer enough for modern applications. Users today expect systems to understand their intent, not just match their characters. I

n this guest post, Suraj Mishra , a seasoned developer and tech enthusiast, dives deep into the world of AI-powered retrieval. He demonstrates how to leverage the power of Vector Search and Elasticsearch to transform a standard Spring Boot application into a sophisticated, context-aware search engine.

Whether you are building for Fintech or E-commerce, this guide will help you bridge the gap between simple queries and true semantic understanding.

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Introduction

Modern applications generate vast volumes of text-heavy operational data, including transaction descriptions, failure logs, dispute explanations, merchant statements, chargeback reasons, and more. Traditional keyword search starts showing limitations in such systems cause searching using an exact keyword rarely works.

For example: