What is Vision AI ?

Core principles and best practices of vision AI for enterprise

At Alteia, we are happy to share our experience and the content you need to enable your digital transformation with vision AI. Here you'll find relevant information about visual data, AI enablement, and the software architecture that is needed to scale your vision AI projects.

Our vision

Vision AI is a category of enterprise software that harnesses advanced AI techniques to transform visual data into business insights. Organizations that deploy vision-based AI can achieve step-function improvements in business processes throughout their value chain, resulting in increased business resilience, greater efficiency, improved profitability, and reduced environmental impact.
Recent breakthrough innovations in AI and machine learning, along with capabilities provided by elastic cloud computing, big data, and the internet of things, enable the development of this new class of enterprise AI applications.

01

An uncharted resource

Gathering visual data is possible with a wide range of commoditized capture devices, such as smartphones, cameras, drones, satellites, and LiDAR systems. These information sources provide very rich quantities of data but lack the structure needed to handle and interpret it, which is why it is so widely underutilized.

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02

A need for a new technology stack

Mastering visual data is at the heart of every large enterprises’ digital transformation, but the challenges before enabling vision AI applications are barriers of entry for many businesses.

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03

The cornerstone of digital transformation

Beyond the challenge of mastering the technical components required to implement AI applications, an organization must master it at scale. This is the heart of every organization’s digital transformation - AI and ML applied to an expertise domain at scale.

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Alteia - Resources

Our approach

Our team gathers state of the art experts, including PhDs and engineers, in multidisciplinary domains ranging from: AI, Machine Learning, MLOps, DevOps, microservice architecture, cloud technologies and infrastructure, allowing an holistic understanding of the entire technology stack.

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