Mage AI vs. WSO2 Integration Platform

Mage is well-suited for probability score for uptake of every product is calculated for customers using ML/ Regression models, choosing customers for a product/ Top products for a customer, based on the requirement and Identifying popular product combinations using association rules from Market Basket Analysis (or affinity Analysis)\Bundle these products as combos.

Incentivized

The best-suited scenario is the service chain pattern or all patterns used in online mode. The less appropriate scenario is a batch service the duration time of the service is more than 10minutes because it is necessary to increase the HTTP timeout.

• Ranking algorithms.
• Cloud-based tool.
• Increase user engagement.

Incentivized

• Service chain pattern
• Message transformation
• Call more than one backend service
• Call service with different protocoll as the client use
• Use file as input
• Use mail as input

• Acquisition Contribution.
• Business Intelligence Reporting.
• Data Destinations.

Incentivized

• View deploy artifact in date time order
• Easy way to map data
• Easy way to manage payload

Mage was the easiest in terms of ease of implementation due to its no-code functionality. However, Mage doesn't have a whole ecosystem like AWS and slightly falls behind there.

Incentivized

We can start with the community version and then when we moved into production we can buy the supported version. The supported and community version have the same code so we can do every test before deciding to buy the supported version.

• Business Understanding.
• Data Acquisition and Understanding.
• Data Modeling and Evaluation.

Incentivized

• Reduce development time to the service integration
• We can use junior developer
• Clustered in easy way