London-based T-DAB.AI, an Artificial Intelligence (AI) company, announced on Thursday, July 21, that it has raised £495K (approximately €581K) in a fresh round of funding to accelerate the development of its Edge AI platform.
Edge AI refers to the installation of AI software in devices throughout the real world. It is called “Edge AI” because the AI computation is done close to the user at the edge of the network, close to where the data is located, as opposed to being done centrally in a cloud computing facility or private data centre.
The capital came from private angel investors such as Growceanu and non-equity funding from the UK’s national innovation agency, Innovate UK as part of industry collaboration with Domin and the University of Bath.
According to T-DAB.AI, the funds will help promote the company’s advanced Federated Learning capabilities, automated Edge ML-Ops, and accelerated deployment mechanisms. The capital will also help the sales and marketing developments of T-DAB.AI.
Ciprian Man, Investor/Founder at Growceanu, says, “We invested in T-DAB because it is a company made up of an excellent team, with people very well trained in business, technology and sales. They have also developed a solid set of innovative products and services in a technical field applicable in many industries, including production, energy, automotive, HVAC and Smart Building. The solution is already validated, the current sales are excellent and have very high traction.”
An Edge AI platform for IoT applications
AI and Machine Learning (ML) are capable of producing high returns on investment across a wide range of industrial applications. But their widespread adoption is constrained by a lack of suitable machine learning infrastructure and the requirement to centralise data, which has a negative impact on cost, privacy, and network availability.
T-DAB aims to remove these obstacles to AI for the Industrial Internet of Things (IoT). The company’s idea is to move the algorithms to the data and learn at the Edge rather than moving data from Edge devices to central cloud platforms. Federated Learning is a technique that combines learning from various devices to produce intelligence. To do this, T-DAB.AI developed OctaiPipe, a decentralised AI platform for industrial IoT.
OctaiPipe is an artificial intelligence that addresses high-value industrial machine intelligence use cases while lowering costs, privacy hazards, and network or cloud dependency. Users have the option of purchasing pre-built solutions or creating custom ones to scale and deploy on OctaiPipe.
Founded in 2016 by Eric Topham and Paul Calver, T-DAB.AI helps to build or buy machine learning solutions trained at the Edge, and push models into production and deploy them faster, privately, and cost-efficiently.
The company’s platform claims to make it possible to integrate Edge AI into IoT infrastructure without having to transfer large amounts of data to the cloud. Consequently, there will be an increase in security and privacy, a decrease in expensive data and compute expenses, and a decrease in the requirement for constant network access for connected device intelligence.
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