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Service Models and Scalability

· 4 min read
Gyulim Gu
Gyulim Gu
Solution Architect

Mellerikat Service Models​

Mellerikat is a powerful tool for digital growth and innovation, combining AI and cloud technologies to optimize enterprise business processes. Through collaboration with various partners, it delivers tailored solutions to enhance customer competitiveness.

The Mellerikat platform is highly flexible, enabling partners to apply it across diverse service models. Each customer can receive services tailored to their specific needs and circumstances, accelerating their digital transformation (DX). This article explores these service models, their operations, and the benefits they provide in detail.

To use Mellerikat, a basic cloud infrastructure is required. The AI Conductor is installed on this infrastructure to manage AI solutions, train data, and generate models. Partners leverage this cloud infrastructure to configure services and deliver solutions aligned with customer requirements.




Service Models​

Report Service​

This service involves deploying all components on the partner’s cloud and reporting the results of AI models. For example, it provides solutions for raw material price forecasting or anomaly detection and root cause analysis based on customer-provided data. Customers can receive essential reports without building their own infrastructure, enabling data-driven decision-making.

Solution Service​

In this model, partners handle MLOps for the AI model, while customers access services via the Edge App. Customers do not need to manage model maintenance; they simply input data into the Edge App to receive real-time AI analysis results. The Edge App can be installed on local computers or existing systems for quick and seamless service access.

Solution Service (Security / Operation)​

For customers requiring data security and direct model operation, the Edge Conductor and Edge App are deployed on the customer’s infrastructure. Partners provide solutions through the AI Conductor to address customer challenges, while customers manage their data to create and operate models. This minimizes data breach risks and allows customers to directly control the AI model lifecycle.

Full Package Service​

For customers prioritizing data security, the AI Conductor is installed on the customer’s Private Cloud. By establishing a dedicated cloud, MLOps can be operated within a fortified security framework, ensuring all data and models are securely managed internally.




Benefits​

The Report and Solution Services enable partners to create workspaces for individual customers within a single AI Conductor, connecting Edge Conductors and Edge Apps to deliver services. This structure allows partners to efficiently serve multiple customers, with reusable solutions and Edge-based deployment reducing service delivery time.

Customers can minimize the time and cost of infrastructure setup and management, focusing on digital transformation (DX) with the services they need. For customers prioritizing data security, services can be securely operated on their own infrastructure, and by directly managing and operating models, they can assume the role of a partner.




Scalability​

By integrating Mellerikat’s cloud infrastructure with Edge Apps, services can be delivered in various forms by deploying Edges across different elements of the business value chain. This enables high scalability across sectors such as product manufacturing, logistics, and customer service.



  • Deployment in Diverse Environments: The flexible installation of Edge enables customers to utilize AI solutions in any location, such as factory floors, logistics centers, or offices.
  • Expansion Across Business Functions: Edges connected to the cloud enable consistent data management and analysis across the entire business, maximizing overall productivity and efficiency. For example, integrated solutions can address quality control in production lines, logistics optimization, and customer service enhancements.
  • Cost Savings: By optimally utilizing resources in a single cloud infrastructure to create and share models, and leveraging local resources at the Edge, costs are reduced. This decreases data transmission costs and optimizes bandwidth usage. Additionally, operations can be sustained without additional infrastructure investments despite expanded service scope.

Mellerikat’s scalability empowers businesses of all sizes to achieve efficient digital transformation, accelerating business innovation.