The Cloneable Platform
Making any device an intelligent extension of your internal experts
Despite the incredible potential of deep tech like AI and IoT, it’s still a struggle to make it truly impactful for businesses. Today, millions of field devices are collecting data on assets around the world, but they're generally uninformed, data collecting machines. They don't know why they're collecting that data, or what to do with it.
Imagine this: a drone that's not just collecting data, but understanding it, categorizing it based on business rules, and taking meaningful action - like dispatching a lineman to assess rust on a transformer.
To extract meaningful information from a person or device in the field, you need:
- Context: What are you looking for, and what do you do when you find it?
- Automation: How can you repeat this process over and over at scale and without variation?
- Technology: How can you apply the right model or tool to solve the business need? This could be an AI model, a proprietary computer vision model, or even something simpler like LiDAR to capture a measurement or GIS to identify a location.
Often, the knowledge behind these requirements is held by different areas of the business. For example, data science may develop models, operations may set the logic to run a field process, and finance may set the financial framework. Each of these groups hold intimate, internal knowledge that must be ‘cloned’, integrated, and deployed to the field.
This is why we built Cloneable; to make any device in the field an intelligent extension of internal experts.
Our platform consists of several modules to eliminate the complexity and costliness of this process, including a drag and drop web interface for building custom apps, an iOS app & SDK for easy deployment and an API for integration with other systems.
Cloneable Builder
The platform's modular and open architecture facilitates easy customization through a library of over 40 pre-built components, covering tasks such as computer vision, natural language processing, and augmented reality.
Components are categorized into UI, processing and logical tasks that users can drag drop to build dynamic apps. Businesses can also craft bespoke components leveraging their IP to align with unique requirements or models.
Cloneable’s builder makes it easy for developers to create complex processes that trigger specific actions like capture LiDAR, run AI model, generate PDF or send notification. Below is an example of a Cloneable workflow that sends a notification to the health and safety inspector whenever a fixed camera at an oil well pad detects a person without their hard hat on.
There are many companies out there developing and training models. We do not train models within our platform, but we've integrated model frameworks as components so that you can upload your models into our system to instantly deploy them into your apps. Models are changing and being created rapidly; this approach allows any user to remove and swap models when the latest and greatest becomes available without compromising existing workflows.
In addition, Cloneable works with your cloud storage. Plug in your credentials and edge devices powered by the Cloneable platform will sync the required files to the device for offline use such as your proprietary AI models, PDF templates, GIS files, and more.
In line with our vision is to democratize access to deep tech, we’re also integrating generative AI to make it possible for anyone within an organization from data science to operations and project management to develop and augment complex business tools.
Easy Deployment
Once a workflow is created, it can be instantly deployed to any iOS device via the Cloneable app in the App Store, or by using our SDK to integrate into an existing app with just a few lines of code.
Once an application is built, it can be deployed on any edge device, starting with iOS and expanding to industrial IoT devices, robots, and drones.
Our entire platform is designed to work in the field with no internet connection. Your app is deployed to the device along with any files and data that it may need while running. As you collect and process data on the device, it will sync back up to the cloud, and across devices as connectivity is regained.
Our platform runtimes are written in native code, allowing us to utilize the full performance of the device. This means being able to process LiDAR in real time and run AI models on video in real time without the need to stream the data to the internet.
The Cloneable platform is a dynamic and expandable layer that makes it easy to extract business value from your mobile and edge devices.
In the Real World
One example of an application that is in testing with Cloneable is the development of an iOS app to support a leading vegetation management company with their manual tree measurement process.
The company had a manual, subjective, and non-auditable process for collecting data associated with tree measurements for vegetation management and utility infrastructure services. This pain was particularly felt by foresters on the ground doing upwards of 50 tree measurements a day, which required measuring a tree diameter with a tape measure, filling out a spreadsheet with tree information, including GPS coordinates and sending it to the Account Manager who would file data and run customer reports. The subjective elements in diameter measurements can introduce discrepancies from forester to forester and many foresters remain reliant on paper maps to track GPS. With Cloneable, the company was able to reduce time spent measuring trees and calculating associated data by 75% with an app that leveraged LiDAR to do instant tree measure, AI object detection to find and classify the tree and PDF creation to store an auditable file of each tree.
For this client, Cloneable worked with the CTO and project management team, but Cloneable can be used by any technical or nontechnical user to build complex applications quickly and cost effectively. We have been working on applications ranging from autonomous infrastructure inspections to running crop models.
Gartner says that 75% of enterprise-generated data will be processed at the edge by 2025, which gets me excited about the breadth of potential applications made possible with our platform. We believe developing and deploying contextual direction to these field devices is how businesses will drive value and scale around these promising technologies.
Tyler Collins, Founder & CTO