Building a Centralized AI Platform Using Lang Chain and Amazon Bedrock

Authors

  • Sukesh Reddy Kotha

Keywords:

Centralized AI, LangChain, Amazon Bedrock, Serverless Architecture, LLM Orchestration, Federated Learning

Abstract

Centralized AI platforms address the growing complexity of deploying, managing, and scaling AI workflows across enterprises. This paper proposes a unified architecture leveraging LangChain for AI orchestration and Amazon Bedrock as the foundational cloud infrastructure. We explore the integration of modular design principles, serverless computing, and advanced Large Language Model (LLM) chaining to overcome challenges in decentralized systems, such as siloed data, inconsistent governance, and operational inefficiencies. Quantitative analysis of throughput (1,200 requests/sec), latency (<200ms), and cost optimization (40% reduction in inference expenses) demonstrates the platform's viability. The paper also addresses ethical AI governance, federated learning, and sustainability, offering a roadmap for enterprises transitioning to centralized AI ecosystems.

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References

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Published

25.02.2025

How to Cite

Sukesh Reddy Kotha. (2025). Building a Centralized AI Platform Using Lang Chain and Amazon Bedrock. International Journal of Intelligent Systems and Applications in Engineering, 13(1s), 320 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/7802

Issue

Vol. 13 No. 1s (2025)

Section

Research Article

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