In 1970, NASA ground control heard “Houston, we have a problem” from the Apollo 13 crew. In an incredible effort of human ingenuity, Apollo 13 team made it back to mother earth after a crippling explosion in space. Please see the Apollo 13 movie if you haven’t.

The movie doesn’t mention the world’s first digital twin that NASA had developed for training and simulation. After the explosion, this digital twin of Apollo 13 served as a sandbox to test different techniques/fixes that astronauts used to return to Earth. NASA’s digital twin saved its twin that was struggling in space.

A Digital Twin is not an inert model. It’s a personalized, individualized, dynamically evolving digital or virtual model of a physical system. It’s dynamic in the sense that everything that happens to the physical system also happens to the digital twin — repairs, upgrades, damage, aging, etc

Since then, the digital twin concept has been applied to many industries. In my career at TIBCO, I helped create digital twins for retailers, airlines, logistics, telcos, banks, insurance, and manufacturers worldwide.

Digital Twins help reduce complexity by distilling relevant data and business context from enterprises’ complex spaghetti of IT systems.

IT spaghetti is getting more spaghettier with the advent of cloud platforms, API’s and applications. Digital Twins enable organizations with a simple and an agile way to develop business applications and optimize business operations.

AI and LLMs (like chatGPT) are helping us create more powerful capabilities in Digital Twins. Imagine an enterprise-grade chatGPT-style chatbot for your business that is trained via your business operations. Imagine being able to auto-generate analytics and applications. Imagine getting the relevant data for your business users/applications in real time.

At AppSteer, we are infusing our no-code capabilities with AI-driven digital twins to build enterprise-grade Retail, Logistics, and Healthcare applications.

Think of a digital twin as a private AI model that learns your company’s operations, transactions, and processes. The value of this is an AI model that is a digital representation of your business, data, and employees/partners/customers.

What does that mean for a customer in retail? It means a digital twin allows retailers to analyze current business performance. You can model scenarios like demand planning, shipment consolidation, BOPIS, dynamic pricing, product recommendation engines, customer 360, and capturing seasonalities and their relationship to product sales.

At AppSteer, our digital twin capabilities include the following:
– Enterprise-grade chatbots
– Auto-generative analytics
– Auto-generative applications
– Federated Learning of AI models

In subsequent posts, I will share more insight into the innovation we are creating to transform the economics of developing enterprise-grade applications.

We at AppSteer thank NASA for developing the concept of a Digital Twin for space vehicles. We are applying it to enterprises worldwide with a boost from AI, LLM, Generative AI, and no-code.