Virtual Assistants - Conversational AI platforms
➢With growth comes the responsibility to serve customers quickly and round the clock.
➢Making availability of services 24 x 7 is a huge cost for enterprises.
➢With ever increasing regulations, customer interaction was getting very long and requiring several more inputs details.
➢The client was looking for a highly scalable economical solution for customer query handling
Analysis & Solution Approach
➢Virtual assistants can help contend with the massive number of support requests for installation, set up, troubleshooting and maintenance, which often overwhelm customer support centers.
➢Using AI, telecoms can implement self-service capabilities that instruct customers how to install and operate their own devices.
➢Speech and voice services are also part of it
➢The solution comprised of a 3-tier architecture solution built using AWS Lex, AWS Lambda and AWS RDS database.
➢The 3-phase project comprised of Requirements Analysis, BOT Training and Implementation & Testing phases.
▪ In the Requirements Phase, process was understood in detail and conversational flow between the customer and BOT was documented in the form of a detailed flow chart.
▪ In the BOT Training Phase, AWS Lex was trained for Intents, Utterances and Slots based on documented conversation flow. Python code was implemented on AWS Lambda Serverless Computing environment to handle the data being captured during the conversation by Lex. Backend database was implemented using PostgresSQL running on AWS RDS.
▪ Once the BOT was trained, it was implemented in production and tested by client extensively. Any testing feedback was incorporated and the Chatbot was made live for end-customer use on top of Client’s web-site. Alternatively, mobile based BOT interface was also provisioned
✓ Several thousand customer queries are now being handled by developed Chatbot solution on a weekly basis.
✓ This has not only made loan query service available to the client 24 x 7 but it has also significantly reduced the costs for the client.
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