Ambli VideoSense
Forget keyword limitations! VideoSense instantly identifies objects within videos, transforming them into shoppable havens. Discover products as you watch, with essential details and purchase options overlaid directly on screen.
Forget keyword limitations! VideoSense instantly identifies objects within videos, transforming them into shoppable havens. Discover products as you watch, with essential details and purchase options overlaid directly on screen.
Ambli VideoSense, the AI-powered search engine designed specifically for video commerce, empowers you to shop directly from your screen. It seamlessly identifies products within video frames, instantly connecting you to similar items available in the linked e-commerce store’s catalog. Discover products as you watch, with details and purchase options conveniently displayed. Effortlessly transition from discovery to purchase without ever leaving the video. VideoSense simplifies video commerce, sparks inspiration, and unlocks a new era of interactive shopping experiences.
Ambli VideoSense redefines video content with the magic of AI-powered search. This innovative technology empowers you to seamlessly shop directly from your screen.
Here’s a concise explanation for each of the 4 VideoSense features:
Access video content and product information in your preferred language.
Don’t just browse – narrow down video search results to find exactly what you’re looking for.
VideoSense learns from your viewing habits and suggests products tailored to your interests.
Discover and instantly purchase products directly within live video streams.
Take advantages of varied Use cases, Choose Ambli to elevate your brand presence.
Limited opportunities for direct product promotion within videos.
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Ambli VideoSense employs object detection and recognition techniques, a subfield of computer vision, to identify objects within video frames. These techniques likely utilize deep learning models trained on massive datasets of labeled video frames containing various objects. When a user watches a video, VideoSense extracts individual frames and applies the object detection model to identify objects within each frame.
VideoSense integrates with e-commerce stores, likely through application programming interfaces (APIs). When an object is identified within a video frame, VideoSense can query the linked e-commerce store’s product catalog to find similar items. Product details and purchase options are then overlaid onto the video screen at the location of the identified object. Users can click on these overlays to access product information and complete purchases directly within the video player.
VideoSense incorporates machine learning algorithms to personalize product recommendations for users. As users interact with VideoSense by watching videos and clicking on product overlays, their viewing habits and preferences are logged. These user interactions serve as training data for the recommendation models, enabling them to identify patterns and suggest products that are likely to align with the user’s individual interests.
Live shopping integration in VideoSense allows users to discover and purchase products directly within live video streams. This functionality likely involves partnerships with live streaming platforms and e-commerce vendors. VideoSense can potentially analyze live video feeds in real-time, identifying products as they appear on screen and displaying similar product information and purchase options overlaid directly on the live stream.
Granular search in VideoSense empowers users to refine their search results within videos. This likely involves combining object recognition with traditional text-based search functionalities. Users can search for specific objects within videos or filter results based on various product attributes like category, brand, or color. This facilitates a more targeted search experience, allowing users to quickly find the products they’re interested in within the videos they’re watching.
AI-powered search solutions for eCommerce platforms revolutionize the way customers discover and interact with products online. By leveraging advanced algorithms and machine learning techniques, these solutions enhance search accuracy, provide personalized recommendations, and improve overall user experience. Features include natural language processing for understanding complex search queries, predictive analytics to anticipate user intent, visual search capabilities for finding products based on images, and real-time updates to ensure product availability and pricing accuracy.
Define the Use case / Problem statement
Prepare the Proposal & Engagement model
Kick-start the Execution and Deliveries