In a recent Gemini Call hosted by the Digital Twin Hub, Mark Bawtree, CEO of SEKAI, unveiled a transformative approach to one of the digital twin industry’s most persistent challenges: the isolation and fragmentation of digital twin deployments. His presentation on cognitive infrastructure offers a compelling vision for how organisations can transform siloed digital twins into collaborative, intelligent ecosystems.
The Hidden Cost of Disconnected Digital Twins
With over 910 registered digital twin companies globally as of early 2025, the digital twin market is experiencing explosive growth across industries. Yet, as Mark highlighted, this proliferation has created an unexpected challenge: organisations are drowning in disconnected digital twin implementations that fail to communicate with each other.
The cost of this fragmentation is staggering. According to research shared during the presentation, organizations lose approximately $3.1 trillion annually in productivity, with employees spending an average of 12 hours per week searching for siloed information across departments and systems. This reality check sets the stage for understanding why cognitive infrastructure isn’t just another technology solution—it’s a critical business imperative.
Understanding Cognitive Infrastructure: The Intelligence Layer
So what exactly is cognitive infrastructure? Mark describes it as “an intelligent layer that connects data, analytics, and human expertise, enabling complex systems to learn, adapt, and make better decisions.” Think of it as the nervous system that allows different digital twins to communicate, share insights, and coordinate actions across large-scale environments.
Unlike traditional integration approaches that require point-to-point connections between systems, cognitive infrastructure creates a unified intelligence layer that sits between backend data sources and frontend applications. This architectural approach is particularly powerful because it can work with legacy systems that were never designed for real-time operations—systems that many organisations have been using for 20, 30, even 50 years.
The Game-Changing Elastic Knowledge Graph
At the heart of SEKAI’s cognitive infrastructure lies what they call the Elastic Knowledge Graph (EKG)—a dynamic, self-healing system that fundamentally differs from traditional static knowledge graphs. While conventional knowledge graphs provide a snapshot of relationships at a point in time, the EKG operates in real-time, continuously evolving and building new relationships as data flows through the system.
This dynamic capability proved transformative in real-world deployments. In collaboration with Siemens Energy, SEKAI demonstrated the power of this approach by creating a comprehensive digital twin for a gas turbine in three months. The real breakthrough? The next turbine took just two hours to implement, showcasing the dramatic scalability benefits of the cognitive infrastructure approach.
Tackling AI’s Trust Problem
One of the most intriguing aspects of Mark’s presentation was the discussion around AI hallucinations and trust. With recent articles from major tech companies highlighting concerns about AI reliability, SEKAI’s approach offers a solution through contextual data management. By ring-fencing data within the cognitive infrastructure and providing rich contextual information, they’ve dramatically reduced AI hallucinations, making AI-driven insights more trustworthy and actionable.
This is particularly crucial for industrial applications where incorrect AI recommendations could have serious safety or financial implications. The cognitive infrastructure ensures that AI models work with verified, contextual data rather than making assumptions based on incomplete information.
Real-World Impact Across Industries
The presentation showcased impressive implementations across multiple sectors:
Manufacturing Excellence
Manufacturing emerged as the most mature market for cognitive infrastructure adoption. Organisations are using the technology to create comprehensive digital twins that span the entire product lifecycle—from supply chain materials tracking through production, training, installation, and ongoing maintenance.
Energy Sector Transformation
With initiatives like Ofgem’s £415 million Strategic Innovation Fund supporting digital twin projects for net-zero electricity and gas networks, the energy sector is rapidly adopting cognitive infrastructure to manage complex, interconnected systems.
Emerging Opportunities
Mark also highlighted growing interest from the retail sector and built environment, where organisations are beginning to recognise the value of connected digital twin ecosystems for everything from smart building management to supply chain optimisation.
The Partnership Paradigm
A key insight from the Q&A session was SEKAI’s collaborative approach to market. Rather than positioning cognitive infrastructure as a standalone solution, they work as part of consortiums, bringing together digital twin companies, visualisation specialists, software integrators, and hardware providers. This ecosystem approach acknowledges a fundamental reality: no single vendor can provide everything a client needs for successful digital twin implementation.
This partnership model is particularly important given what Mark identified as the biggest implementation challenge: organisational resistance to change. While markets in Asia embrace constant change and improvement, Western markets often struggle with the transformational mindset required for digital twin adoption. The UK, however, stands out as having exceptional maturity in digital twin conversations—a promising sign for the technology’s future adoption.
Looking Forward: The Connected Future
As digital twins continue to proliferate across industries, the need for cognitive infrastructure becomes increasingly critical. Organisations can no longer afford to have their digital twins operating in isolation, missing the exponential value that comes from connected intelligence.
The modular, scalable approach demonstrated by SEKAI—where logic patterns can be reused across multiple sites, systems, and processes—points toward a future where digital twin deployment becomes increasingly standardised and efficient. Combined with emerging standards like the Model Context Protocol (MCP) introduced earlier this year, we’re seeing the foundations of a truly connected digital twin ecosystem taking shape.
Key Takeaways for Digital Twin Practitioners
- Think Beyond Individual Twins: Success in digital twin implementation requires thinking about connectivity from day one, not as an afterthought.
- Legacy Systems Are Not Barriers: Cognitive infrastructure can breathe new life into decades-old systems, making them part of modern, real-time digital twin ecosystems.
- Context Is King: Providing rich contextual information dramatically improves AI reliability and reduces hallucinations in digital twin applications.
- Partnerships Drive Success: The most successful digital twin implementations involve multiple partners working together through a unified intelligence layer.
- Start with Pain Points: Focus on specific business challenges rather than technology for technology’s sake—whether it’s reducing time spent searching for information or improving cross-departmental collaboration.
Join the Conversation
The Digital Twin Hub’s weekly Gemini Calls continue to bring together innovators, practitioners, and thought leaders shaping the future of connected digital twins. Whether you’re just beginning your digital twin journey or looking to scale existing implementations, the community offers invaluable insights and connections.
Can’t make the live sessions? All Gemini Calls are recorded and available to Digital Twin Hub community members, ensuring you never miss out on groundbreaking discussions like this one.
The next Gemini Call takes place every Tuesday at 10:30am BST. Join the Digital Twin Hub community to participate in these essential conversations shaping the future of digital twin technology.
Ready to break down your digital twin silos? Connect with the Digital Twin Hub community and discover how cognitive infrastructure can transform your organisation’s approach to digital twin deployment.
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