Applied Computing has entered a strategic partnership with Databricks, aiming to scale its industrial AI foundation model, Orbital, across the global energy sector. Designed specifically for complex operational environments—ranging from refineries and LNG terminals to renewables—Orbital brings domain-specific intelligence that’s built on physics-based modeling rather than generic machine learning.
The integration with the Databricks Data Intelligence Platform allows energy companies to embed these advanced models directly into existing data workflows. By doing so, the partnership addresses a key bottleneck in industrial AI: the difficulty of moving from isolated pilots to scalable, real-world deployments.
Unlike many AI tools still stuck in experimental phases, Orbital is built to deliver real-time optimization with traceability and explainability—critical factors in energy operations where safety, efficiency, and regulation are tightly interlinked.
Dan Jeavons, President, Applied Computing, said: “By combining Orbital with the Databricks Data Intelligence Platform, we can bring superintelligent, physics-grounded AI into the workflows of global energy operators. This is about moving beyond experimentation to real-world impact - reducing costs, improving resilience and accelerating the energy transition. We’re already seeing the real work impact that Orbital can have with customers here in India, and through this partnership with Databricks, we are making Orbital more accessible and easier to adopt for existing Databricks customers.”
Many in the energy industry have struggled to convert promising AI experiments into reliable, cost-saving solutions. Applied Computing is positioning Orbital to change that narrative. Early deployments have shown the model can cut energy use in refinery and petrochemical operations by up to 10%. For large-scale facilities, that translates to millions in annual savings—alongside a measurable reduction in carbon emissions.
The foundation model is tuned to the physics and operational constraints that define energy infrastructure, allowing for more accurate predictions and meaningful system-level improvements. It’s an approach that stands in contrast to more generalized AI models, which often underperform in highly specific industrial settings.
Databricks' Global Energy Leader, Julien Debard, highlighted the demand among energy clients for AI that delivers trustworthy, repeatable outcomes, saying "Applied Computing’s Orbital model represents a breakthrough in industrial AI, and we’re delighted to welcome them to the Databricks Startup and Built on Programmes. Together we can help the world’s most critical industries modernise faster, with data and AI apps and agents they can trust.”
By combining Applied Computing’s sector expertise with Databricks’ data infrastructure, the two companies aim to deliver end-to-end solutions that can be deployed at scale.
