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Databricks Data Intelligence Day 2025

· 3 min read
Keewon Jeong
Keewon Jeong
Solution Architect

Mellerikat Introduced as a Customer Index Platform at Databricks Intelligence Day​

Databricks Data Intelligence Day 2025 Seoul, April 29, 2025, Seoul

At the recently held Databricks Intelligence Day, Mellerikat showcased its Customer Index Platform, completed through a technological integration with Databricks. This platform integrates the entire process from data collection to analysis and AI-based insight generation, enabling a more sophisticated understanding of customers and the execution of corresponding strategies.

During the event, Mellerikat emphasized its role as an insight-driven platform that leads to tangible business transformation, garnering significant attention from attendees.

Customer Index Platform: A New Approach to Understanding Customers Numerically​

Mellerikat's Customer Index Platform derives various forms of 'indices' based on diverse data related to customers. These indices play a crucial role in quantitatively assessing the current state of customers and predicting future behaviors or responses.

For example,

  • Customer Lifecycle Index analyzes the customer journey and relationship strength to predict customer lifetime value.
  • Conversion Propensity Score quantifies the likelihood of a customer taking specific actions (such as purchasing or applying) based on current behaviors and past history.
  • Churn Risk Index helps identify customers at high risk of leaving a service or product early.
  • Customer Value Index quantifies the overall value of customers by integrating various factors such as purchasing power, responsiveness, and loyalty.

All these indices are automatically generated based on AI models and continuously updated according to real-time data flows.

Integrated Architecture Completed through Collaboration with Databricks​

Through its collaboration with Databricks, Mellerikat has significantly reduced the complexity of data analysis and AI model operations while ensuring flexibility and scalability.

  • Data Integration and Governance is implemented through Databricks' Unity Catalog, allowing for consistent management of customer data from various sources.
  • AI Model Development and Operations are automated through Mellerikat's own platform, enabling rapid creation and real-time operation of predictive models.
  • Streaming Analytics allows for near real-time tracking of index changes based on customer behavior or status changes, which can be immediately reflected in actual tasks such as marketing, CRM, and customer service.

Additionally, this platform can directly deploy AI models to edge devices or specific operational systems when needed, effectively functioning in on-premises environments or hybrid infrastructures.

Reasons for Attention at Databricks Intelligence Day​

At Databricks Intelligence Day, Mellerikat went beyond simple technology demonstrations to show how data and AI can enable real business innovation through practical case studies.

Among the presentations, the following points particularly captured interest:

  • Real cases of predicting and responding to churn rates through index-based customer analysis
  • Results of rapidly experimenting and operating AI models based on MLOps, improving marketing campaign performance
  • Methods of discovering hidden patterns in data by handling both structured and unstructured customer data

These cases made attendees realize that Mellerikat is not just a technology platform, but can function as a tool for executing customer-centric strategies.

Key Features of the Customer Index Platform​

Below is a summary of the core functionalities of Mellerikat's Customer Index Platform: