Featured
Experience
Technologies
• Initiated and automated an intelligent customer support desk for Edgenta, streamlining ticket handling, query resolution, and workflow management to improve latency and operational efficiency.
• Established and deployed MT/MX financial message validation systems for large banking clients including HDFC and ICICI, ensuring accurate internal transaction processing, regulatory compliance, and reduced manual reconciliation effort.
• Developed an automated airline helpdesk platform covering flight bookings, trip management, and hotel integrations, providing faster customer support and end-to-end travel assistance.
• Contributed to large-scale automation initiatives at R Systems by combining AI systems, workflow orchestration, and backend integrations to modernize customer service and financial transaction operations.
Featured
Projects
AI-powered business intelligence platform that transforms natural language questions into interactive charts and insights in seconds. Democratizes data analysis for non-technical teams with 95% faster time-to-insight.
Technologies
Vedic intelligence engine grounded in the Bhagavad Gita that delivers philosophical clarity for complex decisions. With 700 verses indexed, an 8-agent reasoning chain, and sub-5-second responses, it turns mental friction into actionable wisdom.
Technologies
About
Me
Vansh Garg
I focus on building production-grade AI systems that move beyond demos and deliver real operational impact. My work centers on RAG pipelines, LLM-powered automation, and agentic workflows that reduce manual work, improve decision-making, and scale reliably in production environments.
Skills
Featured
Blogs
The Art of Starting Over: How to Rebuild Yourself
On losing everything you built, hitting rock bottom, and why starting over might be the most important thing you ever do.
The Definitive Guide to Chunking Strategies for LLMs and RAG Systems
Master document chunking for RAG systems. Learn 5 proven strategies to reduce hallucinations, improve retrieval accuracy, optimize token usage, and build production-grade RAG pipelines that actually work.
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Development