The customer chose to protect their confidential information
In this business case, Andersen's customer was a Kazakhstan-based bank that is particularly active in the mortgage market.
The customer approached Andersen with a request to develop and deploy a scalable AI-driven chatbot that would enhance customer interactions across digital platforms. The chatbot was required to support multi-channel intent recognition for RAG databases, integrating AWS AI solutions for text recognition and document search (for both external and internal use).
Technologies:
Amazon DynamoDB Delivery, AWS Lambda Delivery, Amazon OpenSearch Service Delivery, Amazon S3
The cost-effective and modern solution suggested and implemented by Andersen resolved the following challenges:
Andersen engineered and deployed an AI chatbot for integration into the bank’s digital channels. The solution incorporates LLMs (Anthropic's Claude, Cohere, and HuggingFace embedding models) and enables building REST APIs for text queries and RAG database management. Our team designed a storage structure that was optimized for multi-channel adaptability. Additionally, we enhanced the chatbot's API with prompt engineering to improve content retrieval. The solution is built on a robust AWS foundation and uses, among other services:
Delivered functionalities include:
Outcomes include:
As an official AWS partner, Andersen employs a team of over 50 AWS-certified engineers, specializing in cloud-native development and seamless software migrations. With over a decade of experience in AWS consulting and application development, Andersen has successfully delivered high-performance, secure, and scalable cloud solutions to clients worldwide.
What happens next?
An expert contacts you after having analyzed your requirements;
If needed, we sign an NDA to ensure the highest privacy level;
We submit a comprehensive project proposal with estimates, timelines, CVs, etc.
Customers who trust us