On-Prem AI - AI on own infrastructure

Operating an artificial intelligence (AI) system on its own infrastructure poses major challenges such as high investment costs and the need for in-house expertise. However, it offers many benefits for organizations looking to establish an AI strategy. The solution outlined in this paper illustrates the power and benefits of Juju, a charmed operator lifecycle manager (OLM), to create and manage an AI infrastructure based on its own infrastructure. This infrastructure can support the MLOps of a common AI use case for financial time series data and predictive modeling.

Advantages of an AI solution on own infrastructure

Any organization looking to develop an AI strategy should consider several important criteria. Cost-effectiveness is often one of the most important criteria when procuring and building AI technology and infrastructure. However, other criteria such as flexibility, usability, and security must also be considered to build an effective short- and long-term strategy.

When considering the financial, operational and security criteria, the next decision is whether to build and host the application in a public cloud or on its own infrastructure. Given the cost and difficulty of managing specialized AI servers, and the market tendency to deploy new applications in the public cloud, there are significant advantages to building and operating an AI infrastructure on your own infrastructure:

Building your own private cloud can reduce costs Using public cloud services quickly leads to dependencies. For example, if you Google Services for the development of your Document processing it can be very difficult to remove this application from Google Cloud because it depends on the APIs and cloud services. This example can also be applied to AWS and Microsoft public cloud services.

Sticking with public cloud services is not necessarily a negative, as they offer a rich catalog of applications as well as out-of-the-box AI capabilities that can make it easier to deploy and develop your AI workloads.

The catch is that things can get very expensive very quickly as you move forward on your AI journey. AI development requires a lot of compute resources as well as long-running training jobs (days to weeks) to keep your neural networks useful and up-to-date with fresh data and features. This computing power can be expensive in the cloud, costing 2-3 times as much as building your own private cloud to train and run the neural networks.

On-Premises adopts standard security processes

Many organizations already have established security rules and defined processes that will most likely be broken when they begin their AI journey in the public cloud. Financial and government organizations are good examples of how public clouds may not meet the exact or unique security and compliance requirements that are easier to implement with an on-premise solution.

Costs and resources

One of the biggest problems for organizations looking to use public cloud services for AI is how to use the data they have been collecting for years. If your data is stored on your own infrastructure, the overhead and cost of data transfers can be significant, especially given the enormous size of neural network training datasets. For this reason, it usually makes sense to build your AI on-premises as well.

AI models, NLP, NLU and computer vision in regulated business scenarios.

Konfuzio is an innovative platform that enables AI models, NLP (Natural Language Processing), NLU (Natural Language Understanding) and computer vision to be used for data annotation. It allows new models to be securely trained, published and monitored in regulated enterprise scenarios on their own infrastructure. The full process is described in detail below.

  1. Data annotation: Konfuzio provides a user-friendly interface to annotate data efficiently. It uses NLP, NLU and computer vision to automatically detect and extract patterns and relationships in unstructured data. This significantly speeds up the data cleaning and preparation process.
  2. Model training: After the data has been annotated, it can be used for training new models. Konfuzio supports various machine learning and deep learning models for different use cases. The platform allows models to be trained on the company's own infrastructure and thus retain control over the training environment and the security of the data.
  3. Model Release: Once models are trained, Konfuzio enables the release of models within the enterprise in a secure manner. Model release can be governed by role-based access and access controls to ensure security and compliance.
  4. Model monitoring: After the models have been released in the production environment, Konfuzio provides functions to monitor the performance and usage of the models. This helps to detect problems early and make continuous improvements to the models.
  5. Use in regulated industries: The ability to run the entire process on the company's own infrastructure makes Konfuzio particularly attractive to regulated industries such as financial services, healthcare and government organizations. By adhering to internal security policies and compliance requirements, these organizations can implement AI solutions without compromising on security.

The Konfuzio platform is a comprehensive solution for organizations looking to effectively deploy AI models, NLP, NLU and computer vision in regulated enterprise scenarios. The platform offers high flexibility, ease of use and security, and allows the entire process from data annotation to model release and monitoring to be performed on the organization's own infrastructure. This enables organizations to take advantage of AI technology while maintaining control over their data and infrastructure.

If you are interested in learning more about Konfuzio's capabilities and how it can help your organization successfully and securely integrate AI solutions into your regulated workflows, you should contact Konfuzio. They offer comprehensive guidance and support in implementing the platform and customizing it to meet your specific needs.

    Konfuzio's partners can help you select the most appropriate models and technologies for your specific use cases and develop a customized AI system that perfectly matches your business goals and requirements. They will also help you integrate the system with your existing IT infrastructures and processes to ensure it works seamlessly and efficiently.

    In addition, Konfuzio partners provide training and resources to help your team effectively use the platform and implement AI-powered solutions. This ensures that your business can realize the full potential of AI technology and that your team has the expertise needed to make data-driven decisions and drive innovation.

    Overall, Konfuzio provides a complete solution for organizations looking to deploy AI models, NLP, NLU and computer vision in regulated enterprise scenarios. With a focus on security, flexibility and ease of use, the platform enables the efficient deployment and management of AI solutions on their own infrastructure. This gives organizations the ability to take advantage of AI technology while maintaining control over their data and systems.

    Don't wait any longer to take advantage of AI technology for your business. Contact the Konfuzio team today to find out how their platform can help you optimize your business processes, make informed decisions, and increase your competitiveness in the marketplace.

    Edwin Genego Avatar

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