What if AI could learn the physics that drive optimal product performance?
Introducing Generalized Physics Informed AI

TECHNOLOGY

The Most Advanced Predictive AI Technology in the Market

Generalized Physics Informed AI uses advanced mathematics, novel neural concepts, and physics informed machine learning (PIML) approaches that:

  • Have Higher Predictive Accuracy: Are both physically and scientifically consistent thus increasing their predictive accuracy.
  • Use Less Data: Require an order of magnitude less data to be trained.
  • Converge Faster: Arrive to an optimal solution faster.
  • Provide Extrapolating Insights: Are highly generalizable, thus enabling them to make prediction for unseen scenarios.
  • Are Explainable: Are transparent and interpretable, thus making them explainable and trustworthy.

SOLUTIONS

A Unified Predictive AI Framework That is Fast and Accurate

PredictiveIQ offers a Generalized Physics Informed AI solution that enables Accelerated Engineering and Optimized Performance.

In Accelerated Engineering, time consuming engineering simulations like CFD analysis are transformed into fast and highly predictive AI models, thereby allowing engineers to explore design alternatives and optimize products

In Optimized Performance, data-intensive analytics like the ones used in predictive maintenance digital twins are transformed into predictive AI models that use only a fraction of this data, thus greatly improving predictive insights and reducing big data pains associated with data management and storage.

Generalized Physics Informed AI Enables Engineers to Accelerate and Optimize Product Designs

Generalized Physics Informed AI Enables Operators to have Predictive & Prescriptive Product Performance Insights

Breaks the Engineering/Performance Barrier

ABOUT US

Engaging Vision

About Us - Engaging Vision

Traditional digital transformation efforts focus around connecting assets, adding sensors, and managing large amounts of data. This data needs to be collected, stored, aggregated, labeled, and then transmitted to some cloud environment for “Big Data” algorithms to then make sense of this massive ocean of data.

In order for machines to be truly smart and autonomous, they must be able to predict in real-time on platform or on edge, machine performance under very complex environments. This is simply not practical under traditional cloud-centric “big data” data analytics paradigms.

At PredictiveIQ, our vision is making truly smart and autonomous a reality through our groundbreaking predictive ML/AI technologies that reduce data requirement for orders of magnitude and our business-centric solutions that are aligned to key business processes.

Contact Us

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