The Tangent Information Modeller
TIM, or Tangent Information Modeler, is an automatic predictive model building engine that automates the forecasting and anomaly detection process by analyzing time series data and generating accurate models based on the patterns it detects.
Often, data scientists create handcrafted models to see to companies’ analysing needs. In crafting these models, they go through the processes of data preparation, model building, model deployment and execution. It quickly becomes clear that this is a difficult and laborious task, and while results may be good, they are not scalable.
In come AutoML techniques, which train many different models and then select the most successful out of them. While this is a great step towards automation, tedious, manual feature engineering is still required, which calls for the input of a domain expert. The result is a compute-intensive trial- and-error process that can take up weeks of valuable time.
TIM goes beyond these methods with its InstantML technology. With InstantML, a model is created in one single step, including feature engineering, model building and model deployment. All of this is automated and happens under the hood of the TIM engine. The user provides input data and TIM responds with the necessary models, that can be applied to the desired forecasting and anomaly detection purposes.
With the unique RTInstantML technology, TIM goes even further. RTInstantML automates everything from model building to model application, taking input data and directly providing the user with the relevant forecast. This eliminates the need to set up a particular data availability situation, as the situation can be extracted directly from the input dataset at the time of forecasting.
Thanks to TIM’s thorough automation of the model building process, no data scientists are required to get great results. Rebuilding and retraining models becomes easy and users can even leave model storage completely out of the picture with TIM’s RTInstantML technology. All of these features are brought together into a scalable architecture.
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.
For users who desire full control over TIM’s modelling parameters
For users looking for a more streamlined graphical interface
TIM Clients or TIM on platforms:
For users who want to implement TIM directly in their favourite tool or platform
Upload your dataset with the target variable and predictor candidates. Explore it and get valuable insights.
Experiment. Go through parameters to finetune settings in an iterative way or let TIM to do the work automatically.
Explore models, accuracy, forecasting situation and predictors importance. Dive deep into models and understand their features.
Turn experiments into Production setup. Use it in production inside TIM Studio web interface or integrate with existing applications via API. Rely on power of TIM’s ML Ops features.
Upload your data into TIM Studio and explore it.
Find the best settings in Experiment Workbench.
Understand the models with TIM’s “explainable AI”.
Production setups, ML Ops.
The Challenge — How to leverage AI technology to improve operational efficiency.
Forecasting and anomaly detection are essential for most businesses since managers must always try to match supply and demand and make their operations run as smoothly and
The Challenge — Meeting the demand for AI-based
forecasting and anomaly detection.
Your organization would like to jump on the AI bandwagon but there is a shortage of data scientists and there’s a tremendous backlog of projects awaiting resources. You’d like to be able to innovate and leverage AI/machine learning technology without needing to be an expert.
TIM delivers — Accessible, accurate AI with fast time to
TIM automates the model generation process so you can create and update predictive models without being an AI expert. So instead of using one generic model to fit a class of customers or equipment, you can create individualized models for each customer or asset, and get the best possible accuracy.
The Challenge — Hosting compute-intensive AI tools and integrating them with your existing databases and applications.
Some AI tools are very compute-intensive and require a major investment in on-premise hardware or cloud instances. You’ve likely got plenty of existing databases, data historians, BI tools and enterprise applications that would likely need to interface with a new predictive analytics tool. Firewall restrictions may make cloud-based solutions impractical.
TIM delivers — maximum compute efficiency, rapid integration and flexible deployment options.
The Challenge — Improving your productivity so you can
focus on the most important tasks.
It’s hard to recruit and retain data scientists these days so your job security is better than ever. That’s the good news. But with a long list of potential AI use cases in your company you may not be able to get the help you need to scale up the use of predictive analytics beyond a small number of projects.
TIM delivers — Scalable, automated, understandable AI
TIM Improves your productivity by eliminating repetitive, trial-and-error modeling tasks and by helping you visualize your model with an intuitive heat map that shows the relative influence of all your input variables. Unlike other modeling tools that require you to choose from
hundreds of pre-defined models, TIM creates an optimized model based on the patterns it detects in your time-series data. You’ll spend less time doing feature engineering, building and explaining models and more time on exploiting the power of predictive analytics across your organization.