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Ranganayak Meravath
Mid-level Generative AI Engineer specializing in RAG, agentic copilots, and regulated AI
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Senior engineer who built and productionized an Azure-based Enterprise AI Copilot for financial/compliance teams, focused on grounded, auditable answers with citations to reduce hallucinations in regulated workflows. Experienced designing multi-step agent orchestration and improving reliability through targeted iterations (e.g., fixing chunking/parsing to materially improve citation accuracy), plus building defensive pipelines for messy ERP/operational finance data.
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Key Strengths
- Shipped an enterprise compliance copilot to production in a regulated financial environment
- Designed systems to minimize hallucinations via grounding in enterprise documents with citations
- Built multi-step agent workflows (ingestion → retrieval → reasoning → validation → response generation) rather than single-pass prompting
- Improved onboarding time by ~60% for policy onboarding/new policy rollouts
- Improved consistency of compliance answers by reducing analyst-to-analyst variability
- Diagnosed and fixed citation reliability issues by refining document parsing/chunking to preserve section boundaries
- Strong production mindset: monitoring, governance, failure-mode handling, and defensive data pipelines for messy ERP-like data
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