Use vector search to find, sort, and filter what you need in your unstructured data

Our Smart Search feature leverages vector search capabilities to power the search experience.

Available directly on the Input-Manager screen, it enables you to seamlessly search through both structured and unstructured data by leveraging AI to surface the most relevant results with ease.

Note: The Inputs-Manager screen is the main page showcasing all the inputs in your app. You can access it by clicking the Inputs option in your app's collapsible left sidebar. The screen has two modes: Input Mode (default) and Object Mode.

When performing a Smart Search with custom concepts, ensure that these concepts are first trained using an embedding-classifier model ( transfer-learning model). Without this training, the search query may not work. On the Inputs-Manager screen, concepts that have already been trained with a model are marked with a blue circle, while untrained concepts are marked with a grey circle.

Types of Smart Search

We offer the following types of Smart Search options in our platform.

• Smart Image Search — Allows you to retrieve images sorted by their visual relevance to a query in the form of:
  • Image — Provide a reference image of interest to compare inputs against.
  • Concept — Provide a trained concept to compare input predictions against.
  • Caption — Provide a full-text description to compare inputs against.
• Smart Object Search — Allows you to retrieve annotated objects (bounding boxes within images) sorted by their visual relevance to a query in the form of:
  • Image — Provide a reference image of interest to compare inputs against.
  • Concept — Provide a trained concept to compare input predictions against.
  • Caption — Provide a full-text description to compare inputs against.
• Smart Text Search — Allows you to retrieve text data sorted by their content and semantic similarity to a query in the form of:
  • Text — Provide a text description to compare input predictions against.
  • Concept — Provide a trained concept to compare input predictions against.