From Raw Data to Personalized Advice: An Agentic AI Framework on AWS Lambda for Real-Time Financial Planning
DOI:
https://doi.org/10.56127/ijst.v2i3.2331Keywords:
Serverless Architecture, Amazon Bedrock, Agentic AI, AWS Lambda, Event-Driven Systems, Financial Planning, Real-Time Data, Personalized AdviceAbstract
The increasing need of personalized and real-time financial planning has shown gaps in traditional advisory systems which rely more on rule-based automation and as a rule using mostly fixed form models. The paper introduces a new serverless design that builds upon agentic artificial intelligence (AI) that is orchestrated using Amazon Web Services (AWS) Lambda to offer dynamic, cost-effective, and scalable financial insights. The proposed framework enables quick access and contextualization of customer-specific financial data by combining Amazon Bedrock as contextual language understanding and distributed data storage providers, AWS S3 and DynamoDB. Amazon EventBridge allows the seamless end-to-end orchestration, allowing the transformation of raw financial information into actionable advice with a low latency. This paper does not only show the technical feasibility of the approach, but also its economic and societal implications, such as scalability, cost optimisation, and democratization of expert-level financial planning. The framework in addition to operational efficiency emphasizes on a customer focused design to promote accessibility and confidence in financial decision making. The findings suggest that the developed system is not just another example of a chatbot system, but it provides adaptive and contextually sensitive financial guidance and, therefore, the proposed system is an impressive improvement in the financial technology infrastructures.
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