HawkSearch offers multiple Smart Search types designed to enhance discoverability, accuracy, and user experience. These search methods leverage advanced AI, natural language processing, and visual recognition to optimize search results. Below is a comparative analysis of the available Smart Search types:

Comparison Table of Smart Search Type

Search Type	Input Type	Core Functionality	Use Case
Concept Search	Text (string-based query)	Uses AI-powered Natural Language Processing to understand the context and intent behind search queries, retrieving conceptually relevant results even if exact keywords are not present.	Enhances search accuracy by interpreting user intent beyond keywords, ensuring meaningful results.
Visual Search	Image upload	Utilizes image recognition to analyze image content and find visually similar items.	Helps users find visually similar products or content when they have an image.
Image Search	Text description of an image (string-based query)	Uses image recognition and Natural Language Processing to match textual descriptions with the most relevant images.	Allows users to describe an image without needing an exact reference, improving search accuracy for visually-driven queries.
Unified/Hybrid Search	Text (string-based query)	Seamlessly integrates Keyword Search, Concept Search, and Image Search, dynamically selecting the best search method to maximize relevance and minimize zero-result cases.	Ensures a frictionless and comprehensive search experience by combining multiple search approaches.