Summary
Retail sales amounts to 41 billion euros per day all over the globe; e-commerce revenue in Europe is expected to grow from 292.2 billion U.S. dollars in 2017 to 499.5 billion U.S. dollars in 2024.
To help our retail clients tackle the problems mentioned and also seize these opportunities, we are set to democratize Artificial Intelligence innovation in retail, by developing a technology capable of handling together small data bundles and produce valuable high quality customer knowledge, spending patterns, and an overall array of information potentially predictive and thus strategic.
Our innovation idea, X-AIR, is to explore the feasibility of this network’s potential to be a source of knowledge, by leveraging PaperVault’s technology with AI & Machine Learning (ML) tools and expertise, and to become a vehicle for an affordable AI integration in retail stores, offering them new ways to improve the customer experience and to optimize operational efficiency and productivity.
In short, X-AIR goal is to expand our current portfolio, gain market share but also to reach new markets, offering solutions not yet available.
The IA will report to the CEO and lead the research into the potential of our current technology to help retailers overcome access barriers to customer knowledge.
To help our retail clients tackle the problems mentioned and also seize these opportunities, we are set to democratize Artificial Intelligence innovation in retail, by developing a technology capable of handling together small data bundles and produce valuable high quality customer knowledge, spending patterns, and an overall array of information potentially predictive and thus strategic.
Our innovation idea, X-AIR, is to explore the feasibility of this network’s potential to be a source of knowledge, by leveraging PaperVault’s technology with AI & Machine Learning (ML) tools and expertise, and to become a vehicle for an affordable AI integration in retail stores, offering them new ways to improve the customer experience and to optimize operational efficiency and productivity.
In short, X-AIR goal is to expand our current portfolio, gain market share but also to reach new markets, offering solutions not yet available.
The IA will report to the CEO and lead the research into the potential of our current technology to help retailers overcome access barriers to customer knowledge.
Unfold all
/
Fold all
More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/957080 |
| Start date: | 01-09-2020 |
| End date: | 31-12-2021 |
| Total budget - Public funding: | - 134 268,00 Euro |
Cordis data
Original description
Retail sales amounts to 41 billion euros per day all over the globe; e-commerce revenue in Europe is expected to grow from 292.2 billion U.S. dollars in 2017 to 499.5 billion U.S. dollars in 2024.To help our retail clients tackle the problems mentioned and also seize these opportunities, we are set to democratize Artificial Intelligence innovation in retail, by developing a technology capable of handling together small data bundles and produce valuable high quality customer knowledge, spending patterns, and an overall array of information potentially predictive and thus strategic.
Our innovation idea, X-AIR, is to explore the feasibility of this network’s potential to be a source of knowledge, by leveraging PaperVault’s technology with AI & Machine Learning (ML) tools and expertise, and to become a vehicle for an affordable AI integration in retail stores, offering them new ways to improve the customer experience and to optimize operational efficiency and productivity.
In short, X-AIR goal is to expand our current portfolio, gain market share but also to reach new markets, offering solutions not yet available.
The IA will report to the CEO and lead the research into the potential of our current technology to help retailers overcome access barriers to customer knowledge.
Status
CLOSEDCall topic
INNOSUP-02-2019-2020Update Date
27-10-2022
Images
No images available.
Geographical location(s)
Structured mapping
Unfold all
/
Fold all
