CASE STUDY
Industry
Telecom
The client is an American telecom giant. The client uses various SMS gateway providers to quote their customers who wanted to utilize SMS gateways.
In the process, a few prices for a specific model may have changed in the last hour, but the client was still charging them at the previous rates, resulting in some real-time losses.
The pricing of each gateway is dynamic, and there is no way the volatility can be handled in the existing system, where everything is batch processed.
The solution was to provide an optimising and adaptive routing process for cost selection on a real-time basis.
In our analysis, we identified this problem and proposed a real-time solution to the client.
AWS MSK, AWS lambda functions, an AWS S3 bucket, Snowflake, AWS MemoryDb, and Java API are used in the data pipeline. The complete infrastructure is built on the AWS cloud platform. The process takes real-time cost and updates the cache in real-time so that the API can fetch the latest cost and the system can select the correct gateway and network for optimized routing.
AWS MSK, AWS lambda functions, an AWS S3 bucket, Snowflake, AWS MemoryDb, and Java API are used in the data pipeline. The complete infrastructure is built on the AWS cloud platform. The process takes real-time cost and updates the cache in real-time so that the API can fetch the latest cost and the system can select the correct gateway and network for optimized routing.
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