Why Nextspace

Why Nextspace?
Because when data informs decisions, there’s less waste and improved efficiency. It’s why we exist: to help people unify, visualize, and understand their data.

25 years
in the making

Our approach is informed by 25 years of building digital twins for companies like Boeing, Lockheed Martin, NASA, SpaceX, Chrysler, Siemens, Sikorsky, Fiat, Volkswagen, Caterpillar and others.

We came up against hundreds of obstacles in that time and made many mistakes we see others still making today. It’s why our platform delivers against the demands of real-world challenges.

Data first

Choosing Nextspace as a digital twin platform is a choice to put data first, assigning global unique identifiers (GUIDs) to individual components and clearly establishing the relationships—or ontology—between those components.

This GUID-based ontology is core to twins built using Nextspace. It allows twins built on Nextspace to easily scale from a single asset to whole cities or countries, and enables a connected network of individual digital twins.

Easy,
and affordable

Digital twins may have launched at NASA, but we believe everyone should benefit from them. This means making them easy and affordable.  

Easy

Fitting in around existing business systems so you don’t have to change what’s already working for you.

Easy

The ability to import all data formats including paper. To access data locked away in different silos. To utilize data that remains incomplete. To adapt to any data standard once agreed, but not needing a data standard to get underway. 

Easy

For anyone to see and understand data using their choice of three different visualization engines.

Affordable

Priced to enable ROI at any stage of your journey—from first files through to enterprise or government–sized projects.

Open

A standard of openness. 

No proprietary file formats.
No manipulation of source data.
Any browser.
Any cloud server.
Export your data at any time.
‍
Monthly commitments,
unless longer commitments suit you better.

Extensible

We are API-first.

Beyond white-labeling and customizable user interface designs, developer licenses allow specialist functionality and solutions to be developed.

Built to last

Some assets last hundreds of years, so digital twins built on our platform do as well. 

Our platform works from asset planning to disposal due to a framework that is both agnostic and adaptable to new data formats and new technologies. 

Our platform enables seamless handover between different teams, across companies, decades and generations apart.

Digitial Twin Framework

Descriptive
Visual replica
3D geospatial model
Geolocated data
Multiple visualization options, including Cesium, Unreal Engine, and NVIDIA Omniverse
Informative
Broad source data integration
Ontology and GUID management
Attribute display
Document and multimedia integration
Performance and state visualization
Unified data search and discovery tools
Temporal data management and display
Interactive
Connect data using API microservices
Data modification at an asset level
Updates back to source
Augmented, virtual and mixed reality
Intelligent
AI for automated data acquisition and structuring
AI for data analytics
AI for patterns and warning
AI for automated contextualization of data
AI for federated data learrning
Predictive
Physics–based modeling
Real-time scenario planning
Predictive analysis
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We believe digital twins can be divided into five essential categories.
‍
This framework informs the strategic advice we give our partners, as well as our own development roadmap.

Within each category we gather insights to help our partners create digital twins with purpose—active and integrated into everyday processes and reporting; delivering return on investment.

First, identify your ideal twin

The framework allows you to confirm what kind of digital twin is fit for your individual purpose. One challenge may require an Interactive Twin, another a Descriptive Twin.

Despite Hollywood and media hype, most challenges will not require the development of a Predictive Twin. However, each twin category does require the preparatory work undertaken in the category to its left. For example, to create an Intelligent Twin, you first need to prepare to create an Interactive Twin.

Layer and learn over time

This framework encourages a smart start, building your ideal twin by layering data and learning over time. This iterative development creates stronger, more effective digital twins. Our platform user interface and our account license pricing are designed to encourage you take this journey.

Federate different categories

Any category of twin created on the Nextspace platform can be connected to—federated with—any other category of twin regardless of the platform used to create that independent twin.

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