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Laasya Muktevi
Intern Machine Learning Engineer specializing in forecasting, NLP, and RAG systems
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About
Intern who built and deployed a production LLM-powered contract analysis system for finance teams: Azure Document Intelligence for text/table extraction plus Gemini prompting to surface key terms and risks via an async API and simple UI. Emphasizes reliability in production with fallbacks, guardrails against hallucinations, and operational concerns like latency/cost/versioning, delivering summaries in under 30 seconds instead of hours.
Experience
Education
Key Strengths
- Built and deployed LLM-powered contract analysis workflow end-to-end (extraction → LLM summarization → API → UI)
- Improved contract review turnaround from hours to under 30 seconds
- Handled messy PDF extraction with confidence thresholds, fallbacks, retries, and batching
- Designed prompt/workflow guardrails to reduce hallucinations and stabilize outputs across contract styles
- Production-minded deployment focus (latency, cost, and versioning for long documents)
- Strong orchestration experience using Airflow (DAGs, sensors, retries, SLA monitoring) for reliable ML/data pipelines
- Reliability-focused evaluation approach using ground-truth datasets, stress tests, and step-level validation
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