TIM , Tangent Information Modeler, is a predictive modeling engine that automates the forecasting and anomaly detection process by analyzing time-series data and generating accurate models based on the patterns it detects.
TIM can be deployed as a standalone Cloud-based Web application or as a
Web service that can be easily integrated with your existing business
applications through a simple API. Your TIM-enabled end to end solution
can be deployed entirely in the cloud, on premise, or using a hybrid
To build a model, all you need to do is feed your historical data into TIM, and
in just minutes it creates a predictive model ready for validation and
There’s a lot of buzz about AI these days, and technologies like Deep Neural Networks (DNN) or Convolutional Neural Networks (CNN) are often mentioned in the news.
While these techniques are great for image classification and speech recognition applications, they don’t work very well on time-series data that is the basis for energy forecasting, anomaly detection and predictive maintenance.
Applications where TIM really shines.
TIM’s “secret sauce” is based on a field of mathematics known as “information geometry”, which was originally developed in Russia and Japan in the 1950s-1980s, but only recently put into practice by Tangent Works. You’d have to be a research mathematician to understand the underlying concepts, but if you’re curious about terms like “Riemannian manifold”, “Bayesian inference” and “Tangent space”, you can look it up on Wikipedia. The real proof of TIM’s technical approach is that it just works. Hence the company name, Tangent Works.
Automatic model generation for time-series goes hand in hand with anomaly detection. TIM generates high quality models over the in-sample training data. Moreover, TIM’s anomaly detection module estimates distribution density functions of each explanatory variable and checks whether the incoming values in production (out-of-sample) have the same characteristics. If not a data / anomaly warning is dispatched to a user. The anomaly detection module can also be used in a standalone scenario to detect anomalies in your data.
Prepare your data file with the target variable and predictor candidates
Use the Web user interface to select a file to upload
TIM™ shows you the available time range for the target variable- in this case, 1 year
TIM also shows you all the potential predictors in your data set, e.g. humidity, temperature…
Click “Build” to generate a model for the selected target variable.
TIM then analyzes your data and creates the optimal model in seconds using a mathematical approach called information geometry
TIM calculates the mean absolute percentage error (MAPE) for your model, which is a measure of its prediction accuracy
View a visual map for the model showing the relative weighting and relationship of the predictors with the target variable.
In this example, need help to explain what two of the boxes mean
View the summary of the forecast in Microsoft Power BI or any other data analysis tool
Explore the model and data
View the predicted target value and predictors over the specified future time period
Your model is now ready for deployment as a standalone Web interface or integrated with your existing IT applications
Load the data into TIM.
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Automatically build an accurate model.
Understand the model with TIM’s “explainable AI”.
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Deploy the model in your predictive analytics application.
TIM can be used as a cloud service managed by Tangent Works. This offers you ease of use and deployment.
TIM can be deployed on your own Microsoft Azure subscription.
TIM engines and applications can be deployed on your own IT infrastructure. The state of the art container-based architecture allows for easy installation and integration in your environment with minimal effort.
TIM can be deployed on various IoT edge devices. This allows you to bring model building, advanced forecasting and anomaly detection to the field.