Applied Computing unveils the next generation of Orbital at ADIPEC, the first-ever world model for energy. Nov 03, 2026, 11:15 ET * Orbital 2.0 by Applied Computing is built on a first-ever world model for energy that learns cause and effect across a whole plant, rather than patterns in data. * Every customer gets their own world model that runs and evolves inside their own environment. Their data and models never leave. * Energy operators running Orbital can see the plant-wide impact of every decision before they make it, so they can push production higher while keeping the plant reliable and safe. * The launch follows Applied Computing's $20 million Series A in July 2026, led by KBR with participation from Databricks Ventures. ABU DHABI, UAE, Nov. 3, 2026 /PRNewswire/ - Applied Computing, the British AI company building AI for energy operators, today unveils Orbital 2.0 at ADIPEC 2026. Orbital 2.0 is rebuilt on a world model architecture, and puts the power to shape it directly in the hands of users. A world model for energy The first version of Orbital learned patterns in a plant's data to carry out fixed tasks. The new Orbital by Applied Computing is built on a world model that learns cause and effect instead: how mass and heat move through every connected piece of equipment, and what that means for the plant's output. Because it understands how the plant behaves, rather than memorising patterns, it is no longer tied to a single workflow or task, and it can adapt to whatever an engineer needs. The world model is built on a knowledge graph of the plant's physical interactions and improves itself over time. Every customer gets their own world model that runs and evolves inside their own environment. Their data and models never leave. What's new in Orbital by Applied Computing Orbital is Applied Computing's AI for running energy plants at their physical optimum, every day. It connects to a plant's live and historical data, spots what is going wrong, explains why using the physics of the process, and recommends what to do next. It is already delivering results at some of the world's largest energy and petrochemical assets, and through KBR INSITE(R) it is in use on ammonia and olefins units. Orbital 2.0 by Applied Computing adds capabilities such as: * Dashboards built to order. Engineers can describe the dashboard they want, or pick one of Orbital's suggestions, and Orbital builds it automatically from live plant data without manual intervention. * Apps that run themselves. Recurring work, such as the 8am shift report or a heat and mass balance check, becomes an app that Orbital creates via a simple prompt. * Recursive self-learning. Orbital learns from every interaction and from what engineers tell it directly, so it gets smarter the more it is used, and knowledge about the plant stays when people move on. Together, these changes remove the need for Applied Computing's researchers to tune and adapt the model inside each customer's environment, reducing the cycle time for deployment from weeks to days and allowing Applied Computing to scale deployments concurrently. Moreover, users can rapidly customise and extend Orbital themselves. Callum Adamson, CEO and co-founder of Applied Computing, said: "Our mission is to get every energy system running at its physical optimum, and the fastest way to do that is to put Orbital in engineers' hands. Until now, adapting the model to each plant relied on our researchers. That barrier is gone: Orbital now learns for itself and can be fully customised by the engineers who use it every day. We are bringing it to ADIPEC because this is where the industry comes to decide what the next decade of energy looks like." Dr. Samyakh Tukra, Chief AI Officer and co-founder of Applied Computing, said: "The first version of Orbital learned the patterns in a plant's data. What we have built now is a world model. It learns cause and effect, understands how a plant actually behaves, and gets better every day it runs. A plant is always evolving, and so is the work of the engineers who run it, so Orbital cannot stand still either." About Applied Computing: Applied Computing builds AI for energy operations. Its product, Orbital, is built on a world model for energy that combines physics-grounded intelligence with models across chemical engineering, time-series forecasting and language. Orbital provides real-time optimisation that operators can trust in the most complex environments, from refineries and petrochemical facilities to LNG, wind and hydro. Founded in London by Callum Adamson (CEO) and Dr Sam Tukra (Chief AI Officer), Applied Computing is already working with some of the world's most complex industrial sites. In July 2026, the company raised a $20 million Series A led by KBR, with participation from Databricks Ventures. SOURCE Applied Computing

Energy Institute sets up "Applied AI for Energy" committee. Wednesday, October 28, 2026 Energy Institute launches new industry programme to tackle barriers to AI adoption in energy Alongside partners Applied Computing and KBR, the Energy Institute (EI) has launched a new industry programme to help the energy sector use artificial intelligence (AI) safely, effectively and at scale. The EI's new Applied AI for Energy Committee will bring together energy companies, technology providers and AI specialists to tackle common, non-competitive technical challenges that cannot easily be solved by individual organisations working alone. The programme will be led through the Applied AI for Energy Committee, with Dan Jeavons, President of Applied Computing, appointed Chair, and Andy Webster, Senior Director of Digital and AI Transformation for Sustainable Technology Solutions at KBR, appointed Vice Chair. The Committee held its inaugural meeting at the Energy Institute's London headquarters on 15 October, with members drawn from across the energy and technology sectors. It was agreed that the initial focus will be on developing an AI governance framework for the energy sector, alongside an AI evaluation, assurance and benchmarking framework. Dan Jeavons, Chair of the Applied AI for Energy Committee and President of Applied Computing, said: 'AI is already finding its way into control rooms across energy, but the sector is still working out, company by company, how to test it and trust it. 'The Applied AI for Energy Committee gives the industry a neutral place to build that evidence together, so the people running safety-critical assets can adopt AI with confidence. I am proud to chair the Committee and look forward to working with members from across the sector.' Andy Webster, Vice Chair of the Applied AI for Energy Committee and Senior Director at KBR, said: 'Organisations across energy are working through the same questions on AI independently, and the Applied AI for Energy Committee gives the sector a neutral place to build shared evidence, assurance approaches and professional competence. 'KBR is proud to be a founding organisation, and I look forward to co-chairing the Committee alongside Dan.' Martin Maeso CEnv MEI, Director of Technical & Innovation at the Energy Institute, said: 'AI has huge potential across the energy sector, from improving engineering and maintenance to making operations safer, more efficient and resilient. But there are also common technical challenges around assurance, accountability, skills, data and scaling that companies cannot solve effectively in isolation. 'That is where the Energy Institute - alongside our partners Applied Computing and KBR - can play an important role. The Applied AI for Energy Committee will bring operators, engineers and technology specialists together to pool expertise and develop practical industry guidance people can trust. With Dan as Chair, Andy as Vice Chair and a strong group of energy and technology companies around the table, we now have an excellent platform to turn shared challenges into practical solutions.' The programme will focus on the practical challenges holding back wider adoption of AI and will build directly on the findings of an EI-convened industry forum on sovereign AI for UK energy security in July. The forum identified evaluation and procurement, competence and accountability, data rights and operational assurance as priorities for further work. Its findings have been published in the Energy Institute's new Workshop report sovereign AI for UK energy security - Forum report and recommendations. The report finds that AI is already creating value in areas, but scaling applications into operational environments remains difficult. The Committee will develop and oversee a programme of industry projects, with the aim of producing practical resources including good practice guidance and training. The Committee's work is intended to focus specifically on non-competitive challenges, allowing companies to share expertise on areas such as health and safety, operational practices and wider industry improvement.

Seeq and Applied Computing have signed a commercial agreement to combine Applied Computing's Orbital, a foundation model built for energy operations, with Seeq's industrial intelligence platform. The companies announced the deal on October 13, 2026. Orbital detects and diagnoses equipment and process issues, while Seeq's analytics tools let teams investigate those findings and visualise operational data. The companies say the pairing should improve efficiency, emissions, and reliability. The first use will support INSITE, a digital platform from engineering company KBR that serves the ammonia, petrochemical, LNG, and oil and gas industries. Analysts at KBR Innovation Studio Bengaluru will use Seeq to examine anomalies Orbital flags and write customer reports. The companies also plan to explore a two-way integration between the products.