Streamline AI Agents with DynamoDB and Bedrock Integration
Discover how to unify AI agent architecture using DynamoDB's vector search and Amazon Bedrock to simplify data management.
Tech blog · India · page 3
Deep dives into React.js, AI and ML integration, MERN stack patterns, and lessons from building production applications at scale in India — written by Deepak Kumar.
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Sponsored postsNewHave a dev or AI product? Sponsor a post on this blog.Starts at only ₹999 per postSee how it works →Discover how to unify AI agent architecture using DynamoDB's vector search and Amazon Bedrock to simplify data management.
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About the author
Deepak Kumar
Sr Software Engineer at India Today Group | Aaj Tak
Building scalable web applications and Generative AI systems. Writing about React, Node.js, AI and the engineering lessons from 9+ years of production work.
More about meOpen to senior full-stack and AI engineering roles, and to focused contract work. Delhi NCR or fully remote. I reply within 24 hours.
What I take on
Full-stack product build
React, Next.js, Node, NestJS, MongoDB and MySQL — from idea to production.
AI features that ship
OpenAI and LangChain, RAG, semantic search, content and voice automation.
Architecture and scale
Microservices, real-time pipelines and caching — proven at national news scale.
Founding engineer work
Idea to MVP to scale, with SEO and analytics built in from the start.