Building production-grade AI systems with agentic AI, RAG, and LLM fine-tuning. Currently at myOnsite Healthcare, based in Hyderabad, Telangana, India.
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#1 Track record
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Years Experience
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AI Projects
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Production Systems
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Automation Workflows
#2 Journey
How the career has evolved — engineering foundations into shipped, enterprise-grade AI systems.
Designing production-grade RAG pipelines, agentic AI systems, and HIPAA-compliant AI workflows for enterprise healthcare.
Built multi-agent architectures, LLM fine-tuning pipelines, and enterprise knowledge assistants using LangChain, LangGraph, and vector databases.
Graduated with a focus on Machine Learning, Deep Learning, and Natural Language Processing.
#3 Experience
Building production AI for enterprise healthcare.
Leading AI initiatives for enterprise healthcare — designing RAG pipelines, agentic systems, and HIPAA-compliant AI workflows.
Built and maintained AI systems for document intelligence, real-time notifications, and workflow automation.
#4 Stack
The complete toolkit — from model fine-tuning through to deployment and compliance.
#5 Selected work
8 selected builds — RAG platforms, multi-agent architectures, and fine-tuning pipelines.
Enterprise HR teams lacked a unified AI-powered platform to automate the complete recruitment lifecycle from job creation to employee onboarding.
Impact — Automated 80% of recruitment screening workflows, reducing time-to-hire by 60% for enterprise clients.
Traditional ATS platforms required extensive manual effort for screening, scheduling, and candidate follow-up.
Impact — Reduced recruiter workload by 70% through full automation of screening, scheduling, and follow-up workflows.
Healthcare professionals needed instant access to domain-specific knowledge buried across thousands of clinical documents.
Impact — Reduced clinical document search time by 85%, enabling instant knowledge retrieval across 50K+ documents.
Off-the-shelf LLMs lacked domain-specific accuracy for specialized healthcare and HR use cases.
Impact — Achieved 15-25% improvement in domain-specific task accuracy compared to base models.
Enterprise document processing required manual extraction and classification, leading to slow turnaround and errors.
Impact — Processed 10K+ documents monthly with 95% extraction accuracy, reducing manual effort by 90%.
Logistics operations lacked real-time ETA prediction integrated with visual intelligence for package handling.
Impact — Improved ETA prediction accuracy by 30% through multi-modal context integration.
Database teams spent hours manually optimizing slow SQL queries in production analytics workloads.
Impact — Reduced average query execution time by 40% across analytics workloads.
Social media platforms needed automated content moderation to detect and filter offensive language at scale.
Impact — Achieved 94% F1-score on offensive language detection, deployed in production moderation pipelines.
#6 Credentials
#7 Get in touch
Let's build.
Have a project in mind, or just want to talk AI? Send it straight to my inbox — or reach me at vikramnetha27@gmail.com.
vikramnetha27@gmail.com
Phone
+91 87121 63880
Location
Hyderabad, Telangana, India