SmartClick builds fine-grained custom image classifications, which classify if an object exists in an image. Using as few as five reference images, we create a model to classify objects.
Object Detection & Segmentation
SmartClick can detect any given object in a video or an image in real-time. We use state-of-the-art deep learning techniques, alongside our developed algorithms to localize and track objects in video and images.
SmartClick is capable of detecting more complicated patterns, such as those that take place through time. For example, we can detect what activity a person is doing, analyze emotion through facial expressions, assume a person’s body pose, and sequence of actions.
For our Food Recognition system, SmartClick sets up a camera next to the cashier, where the camera can see the tray of food for each person. From there, we automatically detect what kinds of foods are on the tray and in what quantities. We then calculate the cost and send the information to the cashier’s system.
SmartClick can detect and recognize people with having a minimum of 1 image (the more images we have from a person, the more accurate our detection) of a person’s face. We locate face landmarks on the image of a face and use that to match with a database of previously gathered faces and detect if the person exists in the database. There are 3 ways that this product can be implemented.
Our facial emotion recognition technology has been developed to identify human emotions associated with their facial expressions. Analyzing the movement of facial features and changes in the appearance of facial features, the system instantly codes facial expressions and delivers emotional states.
SmartClick can predict various measures and events from given historical data. For example, we are predicting the probability of a user going default, the probability of churn, the probability of certain ads being clicked, etc. We use Machine Learning algorithms and deep learning to find hidden patterns in the data, which contributes to the prediction. (Supervised Learning)
In this scenario, SmartClick will segment the data into multiple groups based on complex patterns within the data. For example, we group users by similarities of their activities, given the user data. This is done by analyzing the relation within the data in order to detect anomalies of user behavior. We also do fraud detection by applying these technologies and developing domain knowledge, specific to the task at hand. (Unsupervised Learning)
SmartClick is capable of constructing an AI system that provides the best decisions in terms of maximizing a utility like an ad revenue, customer satisfaction, time spent on application, etc. The system learns and evolves through time by understanding patterns of data and adapting accordingly in real-time. This can be used to provide the best suggestions for a certain scenario or have the authority to make decisions.
Churn prediction is aimed at reducing business costs and reducing their customer loss. It uses big data to detect customers who are likely to cancel their subscriptions, thus most at risk of churning. It leads to business savings, regardless of the size of the business. The full cost of churn includes both lost revenue and the marketing costs involved with replacing those customers with new ones.
Monetize Customer Data
Sit back, monitor customer behavior, and instantly monetize it with SmartClick’s automated marketing tactics.
Market With Purpose
Knowing where, how, and when to deliver a message to your audience makes it easier for you to do so and achieve the goal in the message.
All the Data in One Place
Data points from all marketing channels are all managed in one place so the system can make accurate predictions about which markets would bring the best results, saving you the time and money you’d otherwise waste on running test campaigns.
Hack the Customer’s Mind
Engage your customer base and turn potential clients into loyal fans. SmartClick essentially finds out what your customer wants both on a global and individual level, and does so not by asking them, but by using machine learning, which is way more accurate.