Best Digital Twin Software for Databricks Data Intelligence Platform
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Compare the Top Digital Twin Software that integrates with Databricks Data Intelligence Platform as of October 2025
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This a list of Digital Twin software that integrates with Databricks Data Intelligence Platform. Use the filters on the left to add additional filters for products that have integrations with Databricks Data Intelligence Platform. View the products that work with Databricks Data Intelligence Platform in the table below.
What is Digital Twin Software for Databricks Data Intelligence Platform?
Digital twin software is an advanced type of simulation software that generates a digital simulation of a physical asset. Digital twin software is designed to monitor asset performance as well as to run simulations to predict potential outcomes or maintenance that might face the asset. Digital twin software essentially creates a "digital twin" of a real physical asset, which is in effect enabling IoT on the physical asset. Digital twin software is very useful for monitoring machinery and other physical equipment. Compare and read user reviews of the best Digital Twin software for Databricks Data Intelligence Platform currently available using the table below. This list is updated regularly.
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Wizata
Wizata
With Digital Twin & Data Explorer, AI Solutions Builder and Automation of Production features, the Wizata Platform empowers the manufacturing industry to drive its digital transformation and facilitates the development of AI solutions from proof of concept to real-time production recommendations for a complete loop process control through AI. This open architecture platform (SaaS– Software as a Service) acts as an orchestrator of your different assets (machines, sensors, AI, cloud, edge,) and ensures you gather and explore easily your data that stays under your sole control. Control resources invested into AI experiments step by step and prioritize your projects depending on how your AI solutions solve your business pains and improve production processes, their return of investment and according to data science best practices in metallurgy that we developed since 4 years around the world.
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