Combat challenges associated with the volume, velocity, and variety of IoT data


Analytics Server

is the machine learning engine that uses advanced artificial intelligence and machine learning to create, operationalize and maintain advanced intelligence from IoT data.

Platform Analytics

provides native analytics capabilities within composer such as descriptive services and property transforms.

Analytics Extensions

help to extend the analytics functionality available in ThingWorx Foundation through tools and interfaces.


Using sophisticated, artificial intelligence (AI) and machine learning technology, ThingWorx Analytics delivers reliable, actionable insights in real-time to ThingWorx powered solutions. ThingWorx Analytics allows users to go to the next level, embedding advanced, predictive, prescriptive intelligence into the applications they build.

ThingWorx Analytics is tightly integrated with the ThingWorx platform to enable organizations to build smart connected solutions faster, at a lower cost, while using fewer resources. It utilizes simple user-friendly interfaces, visualizations, and easy to use tools – eliminating the need for expertise in data modeling, complex mathematics, statistical analysis, artificial intelligence, or machine learning. This allows users to interpret information faster and make decisions in real-time.




Transform your high-volume IoT data into actionable insights. Operationalize models, predictions, and recommendations across enterprise functions to enhance decision-making with ThingWorx powerful analytics capabilities.


ThingWorx Analytics integrates directly with the ThingWorx Foundation platform. It makes it easy for developers to add sophisticated analytical capabilities to the solutions they build while delivering value to end users by automating complex analytical processes on IoT data.

Powerful Modeling

Very fast environment to automatically generate and evaluate models. Allows data science teams to run more experiments, reaching useful models more quickly.

Fast Development

Because ThingWorx Analytics reads data directly off theThingModel, deployment of anomaly detection and predictive scoring is fast and integration into ThingWorx-powered solutions is seamless.


ThingWorx Analytics is specifically designed to tackle the volume, velocity, and variety challenge of IoT data. It can scale to the largest of data sets and analyze, in real time, changes in data that impact “thing” performance or affect the accuracy of predictions or simulations.


Predictive Modeling

Incorporate supervised machine learning into your IIoT solutions. Extends data science practices with automated predictive and prescriptive modeling. No algorithm expertise is required by users. ThingWorx Analytics learns from historical data and uses AI technology to automatically build, validate, and score advanced analytics models capable of making predictions and delivering optimization recommendations as part of your applications.

Explanatory Analytics

Better understand your IIoT data. Provides a variety of advanced algorithms that let you discover useful patterns and correlations within your data. Explanatory analysis is not required to generate prediction models, but it can provide insights that will improve the models you generate.

Anomaly Detection

Monitor continuous and cyclic data streams to identify unexpected changes in behavior. Uses machine learning technology to observe and learn the “normal” pattern on a signal (single data stream) and then monitors for anomalies (outliers) on each input stream individually. Developers can easily integrate the output of real-time anomaly detection into a solution that help users or systems to take action when abnormal behavior is detected.

Predictive Scoring

ThingWorx Analytics functionality includes the ability to make predictions based on data in the ThingModel. Relevant outcome-based predictions (time to failure, errors per hour, etc.) are easily added to applications by subscribing to events in the ThingModel. Predictive scoring can be deployed closer to the “thing” via edge technology, rather than in the cloud data.

Prescriptive Scoring

Improve future performance and results. Automatically execute simulations to generate recommendations to optimize the performance of your product or process. Works as part of ThingWorx Analytics to identify the key factors causing a given outcome, to recommend the factors (“levers”) to change and to prescribe the optimal variable value by how much to improve that outcome. Prescriptive scoring uses prediction models generated by ThingWorx Analytics or equivalent PMML-compliant prediction model generation tools.

Digital Simulation

Simulate behavior of physical products in the digital world using integrated simulation and other computational providers into your application. Simulation models bring deep product specific knowledge and subject matter expertise. Utilize the knowledge of these models while the product is operating in the real world. Rapidly generate intelligence and insights that can be applied throughout the life cycle, impacting how you service, operate, and improve products.

Descriptive Services

Pre-built calculations and other transformations, useful in both general IoT application development and as a preparation step in changing raw data into useful insights for predictive analytics training and scoring



Below you’ll find answers to our most commonly asked questions.

You can count on personalized support around the clock – by email, live chat, or by joining a live webinar.

What is ThingWorx Analytics and what does it do?

ThingWorx Analytics is a capability in the ThingWorx platform. It enables developers to quickly add real-time patterns, easily detect anomalies, uses predictive analytics, and contextualizes recommendations with solutions. ThingWorx Analytics is for IoT solution developers who are not experts in complex mathematics, statistics, or machine learning.

What role does ThingWorx Analytics have in the ThingWorx Platform?

ThingWorx Analytics is an integrated module of the ThingWorx platform that processes data and produces actionable intelligence. ThingWorx Analytics monitors data streams from connected devices directly via connectivity to the underlying ThingModel. It works with other modules to automate the delivery of intelligence to ThingWorx-powered solutions.

Why would a developer use ThingWorx Analytics?

Using ThingWorx Analytics, developers can quickly add sophisticated, automated, analytical capabilities to IoT solutions built on the ThingWorx Platform. This makes them more valuable to end-users. ThingWorx Analytics does not require expertise in analytical, machine learning, or artificial intelligence to use the technology.