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Manufacturing Data Engine and Manufacturing Connect

Add edge to cloud data visibility across manufacturing operations and empower your manufacturing engineers to optimize production at scale using accessible data analytics and AI.

  • Connect a broad variety of industrial assets and systems to a unified data repository

  • Process, contextualize, store, and visualize factory data

  • Use pre-integrated Google Cloud tools to quickly implement manufacturing-specific use cases


Fuel team productivity

Turns all your manufacturing engineers into data scientists with easy-to-use implementations.

Drive data transformation

Delivers real-time, edge to cloud data access and visibility across manufacturing operations.

Deploy AI in production

Helps factories run faster and smoother by using AI and data to optimize cost and production.

Key features


Manufacturing Data Engine

The foundational cloud solution to process, contextualize, and store factory data. The cloud platform can acquire data from any type of machine, supporting a wide range of data, from telemetry to image data, via a private, secure, and low-cost connection between edge and cloud. With built-in data normalization and context-enrichment capabilities, it provides a common data model, with a factory-optimized data lakehouse for storage. 

Manufacturing Data Engine from Google Cloud

Manufacturing Connect

The factory edge platform co-developed with Litmus Automation that quickly connects with nearly any manufacturing asset via an extensive library of 250+ machine protocols. It translates machine data into a digestible dataset and sends it to the Manufacturing Data Engine for processing, contextualization, and storage. By supporting containerized workloads, it allows manufacturers to run low-latency data visualization, analytics and ML capabilities directly on the edge.


Explore how manufacturers can optimize production and increase quality

Accessible data and easy-to-use AI are key to optimizing production and factory-floor operations at scale.

Use cases

AI-driven operation optimization use cases

Use case
Root cause identification

Quickly identify root causes of quality fluctuations and defects in order to pinpoint beneficial initiatives to increase quality and consistency, eliminate sources of defects, optimize maintenance schedules, improve machine calibration, and offer targeted operator training.

Root cause identification
Use case
Machine-level anomaly detection

Analyze time-series machine data, fueled by the same powerful AI engine that powers Google products, like Search. Tap into a real-time stream of machine sensor data provided by the Manufacturing Data Engine. Detect trends and anomalies as they unfold across multiple sensor dimensions such as noise, vibration, and temperature. Rely on a fully managed, serverless API service to drive various use cases from root cause analysis to OEE optimization.

machine-level anomaly detection
Use case
Predictive maintenance

Deploy a solution in weeks without compromising on prediction accuracy using pre-built ML models. Direct integration with Manufacturing Data Engine helps you to tap into live and historic data and empower your own engineers to develop their own pipelines with our pre-built components. You have global visibility and can shift from facility-by-facility maintenance strategies to a global view on machine health.

predictive maintenance
Use case
In-line quality control

Monitor in-line quality control by aggregating sensor and visual data and simulating parameter changes, combining inspection visual data with in-line sensor data. Leverage imaging data to detect and flag quality issues. Combine it with real-time sensor data to get a view of quality against defined parameters. Use your in-line quality parameter data model and AI tools to model parameter changes and understand the impact on your product quality.

Quality control



Please contact our sales team to discuss pricing for your organization.


Extending the data platform and use cases

On top of the data platform, Google Cloud and its partners are creating a growing set of manufacturing use cases using data analytics and AI-driven optimizations.