Unlocking Edge AI/ML: Revolutionizing Enterprise Automation
Last week we hosted our first webinar to give a glimpse into the future of edge intelligence. Our goal is to meet in an open webinar every quarter, share some of the creative applications our partners and clients are building across industries and demo new components that are advancing the capabilities of the platform.
AI is not a black box. We want to create transparency into the companies, tools and applications that are driving businesses forward and highlight how to build specificity into your edge AI strategy.
In this first webinar, we kept it simple by introducing the two parts of the Cloneable platform: the no-code builder and how those workflows translate to applications in the field.
Drive Innovation without Coding
Gartner predicts that low-code/no-code (LC/NC) tools will power more than 75% of new apps by 2025. One of the most striking developments over the past few years has been the paradigm shift of how complex applications get developed. By democratizing access to edge AI/ML through drag-and-drop interfaces and pre-built modules, Cloneable empowers organizations to bypass the traditional coding barriers and unlock the potential of intelligent devices, regardless of their technical expertise.
We drag and drop components, like lego blocks, to build workflows (the apps) we want to run in the field. Each component is a specific action in an application (parse data, input/output data, pull up a map, run an AI model etc.).
Components can be best understood when we break them down into categories:
UI components within the Cloneable platform provide intuitive interfaces for data capture, review, visualization, and interaction within an app build.
- Display a map
- Capture a signature
- Share a PDF
Logical components allow you to easily apply business logic within your apps.
- Configure and output static data as outputs such as location, text, dates
- Output the total number of items in an array
Processing components typically process data in the background.
- Run an AI model
- Process LiDAR
- Barcode extraction
- Send a notification
When we built the platform, we architected components to be highly intelligent and flexible. Each component knows what kind of data it can send and receive, so it’s simple to connect disparate types of data, logic or technologies in one application.
This democratization paves the way for broader adoption and a more inclusive future for edge AI/ML.
Real-World Validation: Witnessing Edge Intelligence in Action
The webinar wasn't just theoretical; it showcased the tangible impact of edge AI/ML in action. From running multiple AI models (ex. look for people and look for PPE) on an edge device to the more complex (ex. run AI, process LiDAR and pull-down specific business data), attendees witnessed real-world use cases that are already driving value and innovation.
We hope that these live demonstrations can get people thinking about the technology's potential and its ability to address critical business challenges across various sectors from the very simple digital transformation needs to the complex deep tech integration and edge decision-making.
Navigating the Evolving Landscape
Have 20 minutes? Take a listen to the full webinar including Q&A session at the end that tackles:
- If a model was built internally, can it run without sharing the proprietary info with Cloneable?
- My field team does data collection in our company’s app, do you have an SDK we can leverage?
- Is Cloneable able to help digitize current methods of record keeping that are still on a physical form? And can one of your building blocks read text and convert to lets say a PDF?
- How do you see this tool supporting companies as drone BVLOS regulations expand?
We hope this will be a part of your education as you make informed decisions for your own edge AI/ML implementations. Sign up for our developer updates below to get information on future webinars!