Twin-Ops-as-a-Service (ToaaS)
Manufacturing margins low ?
We fuse industrial data fabric, digital twins, and cloud-edge automation to improve your margins
Barrier to entry: Most companies still don’t have a practical roadmap for digitising their field assets. "Budgets are tight, stakes are high, and delaying digital transformation is literally leaving money on the line."
About Us
Committed to cost savings
Our Mission
"To liberate every manufacturer’s “dark data” and turn it into measurable productivity gains by coupling edge-ready digital twins, generative-AI copilots, and an outcome-aligned service model that makes transformation pay for itself.."
Our Vision
"A world of zero-downtime, carbon-smart factories where people, robots, and data collaborate in real time—unlocking safer work, resilient supply chains, and sustainable growth for industry and society alike."
Our Journey
"Together we will : Discover, Design, Build, Train, Deploy, Operate and Optimize"
Green
TWINs
We are seeking to collaborate with experts and partners who have proven experience in data strategy and architecture, particularly those capable of working with complex 3-D models. This includes managing and integrating common formats such as STEP, glTF, Revit, and FBX—while considering file size, update frequency, and IP sensitivity.
We follow industry standards like ISO 10303 (STEP), glTF 2.0, and Asset Administration Shell (AAS) to ensure interoperability and semantic consistency across digital twin implementations. Our model and data catalog is tightly integrated with lineage and versioning systems, such as DataHub and OpenMetadata, to maintain traceability and governance throughout the data lifecycle.
We are looking to collaborate with domain experts across both OT and IT to build robust and interoperable digital twin solutions:
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OT experts will bring deep knowledge of asset behavior, control logic, and safety constraints.
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IT experts will contribute expertise in data infrastructure, integration, cloud platforms, and cybersecurity.
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As Digital Twin architects, we will align the semantic and 3-D models, enable real-time synchronization, and design the simulation logic that bridges physical and digital systems.
We aim to leverage key industry frameworks to ensure interoperability and scalability:
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OPC UA for real-time data exchange from OT systems
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Asset Administration Shell (AAS) for standardized semantic modeling
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MQTT, Kafka, and REST APIs for seamless integration with IT pipelines
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ISO 10303 (STEP) and glTF for consistent and efficient 3-D model interoperability
Security is foundational—we will implement best practices in access control, data encryption, and network segmentation to ensure the safe deployment and operation of all components.
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We are looking in working with experts and partners with experience in Asset Administration Shell (AAS). is the standardized digital representation of an asset, the corner stone for the interoperability of Industry 4.0 components organized in Industry 4.0 systems. Bring in your Asset Administration Shell (AAS) and we integrate with the models
Universities and Research centers can contribute across several high-value areas in digital twin ecosystems:
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Develop next-generation digital twin prototypes, including hybrid models that combine physics-based simulations with machine learning, and federated digital twins spanning multiple sites.
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Validate emerging standards and protocols, such as advanced Asset Administration Shell (AAS) profiles and OPC UA over Time-Sensitive Networking (TSN).
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Operate simulation environments that accurately replicate real-world industrial constraints, enabling safe testing and iteration of digital twin solutions.
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Advance semantic interoperability through research in ontology design and asset knowledge graph development, enabling richer and more consistent data integration across systems.
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Pioneer advanced simulation techniques, including multi-physics modeling, real-time behavioral simulations, and agent-based models for complex system dynamics.
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Facilitate joint industry–academic pilot projects, fostering applied innovation and real-world validation of research outcomes.
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Contribute open-source tools and datasets, such as AAS model templates, 3-D reference test rigs, and reusable connectors, to accelerate ecosystem development.
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Drive public–private standards collaboration, helping align industrial needs with policy and regulatory frameworks.
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Host or emulate Industry 4.0 testbeds, including production lines, energy systems, and smart infrastructure, to enable real-world digital twin testing and validation.
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Operate virtual commissioning labs, where digital twins are tested in simulated environments before being deployed to physical assets.
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Ensure secure digital twin lifecycles, addressing concerns such as model provenance, integrity, and version control.
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Support compliance with industrial regulations, including GDPR and NIS2, by embedding privacy and security principles into digital twin architectures.
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Conduct risk assessments focused on the convergence of IT and OT systems, ensuring resilience, safety, and operational continuity.
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Get Involved
Various ways we can work together
Explore Verticals
Accelerates the Path to Sustainability
Yield optimization (e.g., reducing scrap in battery or turbine blade production) slashes raw material losses—especially critical for high-embodied-energy inputs like lithium, titanium, or rare earths. Predictive maintenance extends equipment lifespan and cuts unnecessary part swaps, reducing embedded carbon and landfill burden. Digital twins model process scenarios to minimize trial-and-error, saving materials and energy in development and scale-up.
GreenTwins
How do these innovations drive the future of clean energy? Reach out !
Our Approach
Discover, Build and Deploy
Discover
Identify overall equipment effectiveness (OEE), Flowsheet, Errors heat map, 3-D scan Matterport to Twin, Identify Assest Adminstration shell (AAS), Edge devices content
Build
Integrating 3-D scans to Twin, add-ons to Assest Adminstration shell (AAS), Simulate and train in physics engine NVIDIA omniverse.
Depoly
Depoly with AWS IoT SiteWise or TwinMaker. Operate with client assest and assist with continous testing and train operators using Human machine interface dashboards