Adapdix lands $8M in Series A funding to help companies take the next steps in the Edge AI performance journey
Edge is a new tech buzzword. No day goes by without another headline about edge computing or edge AI. In a very simple term, Edge computing is what I called “power to the devices.” As enterprises move IT compute to the cloud, latency starts to take place. Edge computing is one of the new ways to address the latency issue associated with processing data in the cloud. Instead of relying on the cloud at one of a dozen data centers to do all, computation is now done at or near the source of the data (for example on devices).
Unlike cloud computing, edge computing systems are not connected to a cloud. Instead, they operate on local devices. Edge computing brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth. Now that a better understanding of edge computing, let’s take a look at edge AI and why it is going to be the next wave of artificial intelligence. The edge computing market is projected to reach 1.12 trillion by the year 2023.
Edge AI combines Artificial Intelligence and edge computing. The AI algorithms are run on devices capable of edge computing. The good thing about this is that the data can be processed in real-time, without having to connect to a cloud. One of the leading startup in this space is Adapdix, a Silicon Valley-based tech startup that offers a software platform which optimizes Artificial Intelligence (AI) and Machine Learning (ML) at the edge. Adapdix has created the first EdgeOps ML platform to allow enterprises to drive performance-based ML/AI at the edge.
Today, Adapdix announced it has closed an $8M Series A funding round to accelerate the growth of its AI-powered automation and control software. The round was led by WRVI Capital, with participation from Micron Ventures and existing investor X2 Equity.
Founded in 2014 by Anthony Hill, Adapdix’s customer-centric Adapdix EdgeOps platform provides previously unmatched performance increases in uptime of equipment, reduction in supply chain and logistics cost, and increases in remote worker control and productivity.
Anthony Hill, Founder and CEO at Adapdix, said, “Enterprise companies are increasingly moving processing power closer to the source of the data to increase model accuracy, reduce network cost and congestion, and latency. The Adapdix EdgeOps™ solution is addressing a significant and growing market need to extract value and control systems at the edge. This investment round will solidify Adapdix’s leadership position in the market and enable more enterprise companies to control their end-to-end operations – and ensure uptime – with real-time predictive analytics.”
Adapdix’s EdgeOps is a software-only solution that combines advanced artificial intelligence and machine learning (AI/ML) analytics with a distributed, edge-based control platform. By enabling control where the AI data is, the edge, Adapdix enables a distributed data mesh ecosystem that delivers the new foundation for customer-centric Edge AI deployments.