Organisations that can leverage Artificial Intelligence (AI) effectively can gain a competitive advantage by automating processes, reducing costs, and improving customer experiences. However, deploying AI can be a challenge, particularly when dealing with legacy systems that may not be compatible with modern AI technologies. In this blog, I discuss how an agnostic platform can help overcome the challenges of AI deployment caused by legacy systems, using our own agnostic platform, Galvia, as a proof point.
Legacy systems, which are often outdated technologies, can pose several challenges to AI deployment. For instance, they may use proprietary data formats that are incompatible with modern AI platforms. They may also have limited computing power, making it difficult to run AI algorithms effectively. Additionally, legacy systems may not have the same data quality standards as modern AI platforms, leading to incomplete or inconsistent data sets.
According to VP Analyst at Gartner, Stefan Van Der Zidjen, “For many organisations legacy systems are seen as holding back the business initiatives and processes that rely on them. When a tipping point is reached, application leaders must look to application modernisation to help remove the obstacles”.
Modernising the workplace
An agnostic AI platform, like Galvia AI, is designed to work with a wide range of data sources and formats, including legacy systems. It is also capable of running multiple AI models and algorithms simultaneously, improving accuracy and mitigating data quality issues.
Our agnostic platform has been designed to help organisations overcome the challenges of AI deployment, regardless of the data source, the format, or the programming language used. With its ability to work with multiple data sources and formats, Galvia AI can extract and process data from a variety of legacy systems, making it easier to integrate with modern AI platforms.
In a recent webinar with our partners Cognziant, Associate Director, James Rowley, called Galvia’s agnostic platform as a “game-changer” for its flexibility and compatibility. Talking to Galvia CEO John Clancy, James commented: “Your platform seamlessly integrates with any environment without requiring a complete overhaul of your existing cloud setup. That’s been really great as it means we can solve problems that universities have been struggling with for years.” Watch the webinar in full here.
Seamless integration with legacy systems
One of the key features of Galvia AI is its flexible data ingestion capability, which allows it to ingest data from various data sources, including legacy systems. Galvia supports structured, unstructured, and semi-structured data formats, making it an ideal platform for organisations like Universities or IT enterprises, with a diverse range of data sources.
“Galvia AI’s agnostic platform architecture ensures that organisations can leverage their existing infrastructure while taking advantage of modern AI technologies.”
Mohammad Waqar, Galvia CTO
Galvia AI is built on a scalable and resilient architecture that can be deployed on-premises, in the cloud, or in a hybrid environment. This means that organisations can choose the deployment option that best suits their needs, without having to make significant changes to their existing infrastructure.
Another significant advantage of Galvia AI is our ability to work with multiple AI models and algorithms simultaneously. This means that Galvia AI can use different models to analyse data, improving accuracy and reducing errors. Galvia’s ability to use multiple models also helps to mitigate data quality issues, as it can use models that are better suited to specific data sets.
Moreover, Galvia provides pre-built and customisable solutions for various industry use cases such as fraud detection, predictive maintenance, and recommendation systems. These solutions can be easily integrated with existing systems and customised to suit specific business needs, making it easier to deploy Artificial Intelligence effectively.
Keep competitiveness
Deploying an agnostic platform, like Galvia AI, can help overcome the challenges of AI deployment caused by legacy systems. Galvia’s ability to work with multiple data sources and formats, and multiple AI models and algorithms, makes it an ideal platform for organisations that have diverse data sources and legacy systems. By leveraging an agnostic platform like Galvia AI, organisations can overcome the limitations of legacy systems and take advantage of the latest AI technologies, improving their efficiency and gaining a competitive advantage.
In conclusion, as organisations continue to seek new and innovative ways to improve their operations, AI is becoming increasingly important. However, deploying AI can be challenging, particularly when dealing with legacy systems. An agnostic platform like ours at Galvia AI, can help overcome these legacy systems challenges by enabling organisations to extract data from various data sources, use different AI models and algorithms to analyse data and integrate pre-built and customisable solutions with existing systems. Thereby making it easier to deploy AI effectively and gain valuable insights from data.
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