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Let’s talk about Vector Search.

Keyword search is so old-school.
Let’s ramp up your search.

Semantic search understands user intent to support user-friendly, intelligent AI content search experiences.

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So what is Vector Search?

Traditional search isn’t enough anymore. Find exactly what you’re looking for.

Traditional keyword search can’t always interpret the context and meaning of words, and can get confused with concepts such as synonyms. Vector search is an advanced search technique that understands the semantic similarity between words and returns more relevant and precise results. Today, organizations have more data than ever spread across both on-premises and cloud systems, making it challenging for users to quickly find the relevant information they need to get work done.

Vector search means you don’t need to rely on exact keyword matches, because it considers the semantic relationships between words and concepts, enabling it to find documents that might be missed by traditional search engines. This includes a variety of content types, including audio, video, images, and more.

Ready to learn more? Read “AI-Powered Vector Search: Unlocking the Future of Content Retrieval” on BA Insight’s blog!

Read the blog

What are the use cases for
Vector Search?

  • Law firms can streamline the discovery of relevant case precedents, legal briefs, and contracts, expediting the research process
  • Healthcare organizations can quickly analyze medical records, images, and research papers to accelerate patient services and medical breakthroughs
  • Financial institutions can more easily detect and flag fraudulent activities by identifying unusual patterns and anomalies
  • E-commerce platforms can enhance product recommendations, analyze user behavior, and improve shopping experiences while increasing sales
  • Content creators use vector search to manage vast libraries of images, videos, audio, and textual content—and locate multimedia assets more quickly
  • Supply chain operators can optimize routes, track inventory, and improve demand forecasting to reduce costs and enhance operational efficiency
  • Talent acquisition companies can match job applicants with job descriptions to streamline recruitment considering explicit qualifications and implicit skills
  • Scientists and researchers can more quickly discover relevant publications, research papers, and patents to support their thesis with comprehensive supporting documentation
  • Social media platforms deploy vector search to moderate content that violates community guidelines

Recorded Webinar:

The Power of Vector Search and Retrieval Augmented Generation (RAG)

In this enlightening session, Jason McCullagh, BA Insight’s Enterprise Search Evangelist, unravels the complexities of Vector Search, assesses its superiority over traditional search methods, and introduces the cutting-edge concept of Retrieval Augmented Generation (RAG).

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Vector Search

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