# Saran Kumar S. - Full Technical Context & Knowledge Base for AI Agents ## Overview - **Name**: Saran Kumar S. - **Title**: Generative AI & Machine Learning Engineer - **Location**: Coimbatore, Tamil Nadu, India - **Contact**: sarankumar131313@gmail.com - **Website**: https://sarankumar.space - **GitHub**: https://github.com/swsarancodes - **LinkedIn**: https://linkedin.com/in/saran-kumar-s-sk13022005 - **X / Twitter**: https://x.com/iamsaranhere - **Medium**: https://medium.com/@sarankumar131313 --- ## Detailed Tech Stack & Technical Proficiencies ### 1. Agentic AI & Autonomous Architectures - **LangGraph**: Stateful multi-agent graph orchestration, cyclical graph execution, human-in-the-loop checkpoints, persistent memory state management. - **Model Context Protocol (MCP)**: Standardized tool integrations, resource management, and decoupled agent environment connectivity. - **Autonomous Tool Use**: Structured function calling with JSON schemas, tool validation, retry mechanisms, and error recovery. - **Context Engineering**: Dynamic prompt optimization, context window compression, and conversational memory architectures. ### 2. Retrieval-Augmented Generation (RAG) & LLMOps - **RAG Architectures**: Self-reflective RAG, corrective RAG, GraphRAG, hybrid dense/sparse retrieval with BM25 and vector embeddings. - **Vector Databases**: pgvector (PostgreSQL), Qdrant, Pinecone, Milvus, ChromaDB. - **LLMOps & Optimization**: DSPy programmatic prompt optimization, TruLens & Ragas automated evaluation frameworks (EVALS), hallucination mitigation, semantic caching. ### 3. Model Inference & Infrastructure - **High-Throughput Serving**: vLLM (PagedAttention, continuous batching), Ollama local deployment, AWS Bedrock serverless endpoints, TensorRT-LLM. - **Deep Learning**: PyTorch, Hugging Face Transformers, LoRA & QLoRA Parameter-Efficient Fine-Tuning (PEFT). - **Backend & Cloud**: Python, FastAPI (async/await, Pydantic), Docker, AWS (Bedrock, SageMaker, Lambda, S3, EC2), PostgreSQL, MongoDB, Golang. ### 4. Full-Stack Delivery - **Frontend & Web**: TypeScript, React 19, Next.js, Tailwind CSS, Framer Motion. - **Backend as a Service**: Supabase (Auth, Postgres, Realtime, Storage). --- ## Complete Project Catalog 1. **Manicule** - URL: https://manicule.online - Tech: Open Source, Markdown - Summary: Open-source markdown editor — fast, minimal, and free for everyone. 2. **Chronicle Seed** - URL: https://chronicleseed.vercel.app/ - Tech: React, Supabase, E2E Encryption - Summary: Digital time capsule enabling users to write encrypted letters to their future selves that unlock at scheduled timestamps. 3. **GoML Review Pilot** - URL: https://gomlreviewpilot.vercel.app/ - Tech: Devstral, Next.js, Supabase - Summary: Model-agnostic code review system — swap Gemini 2.5, Lyzr, Kimi K2, and Devstral without changing your workflow. 4. **RoastMyCV** - URL: https://roastmycv-tau.vercel.app/ - Tech: AI, Next.js - Summary: Resume evaluation tool providing candid, actionable feedback with adjustable critique intensity and ATS scoring. 5. **Job Insight** - URL: https://jobinsightai.vercel.app/ - Tech: Lyzr AI, Next.js - Summary: ATS resume generation and career guidance from live job descriptions. 6. **WeatherMate AI** - URL: https://weathermateai.netlify.app/ - Tech: Lyzr, Gemini API, OpenWeather - Summary: AI weather assistant offering contextual lifestyle and travel recommendations based on meteorological forecasts. --- ## Professional Career History ### goML | Applied AI Engineer (Jun 2026 – Present) - Building production AI systems, agent tooling, and AI delivery pipelines at scale. ### goML | ML Engineering Intern (Jun 2025 – Jun 2026) - Deployed Electronic Health Record (EHR) agent pipelines for automated medical document parsing and classification. - Designed multi-query extraction architectures across relational databases and NoSQL backends. - Built travel booking agent workflows with multi-GDS querying (Amadeus/Sabre) and silent failover logic. --- ## Published Research - **SparseCNNet: Efficient Deep Learning for Rapid Lung Cancer Detection** (IEEE / Springer) - **Predicting Alzheimer's Disease via MRI-Based Modeling** (Journal Publication) - **Book Chapter**: Transforming Data Visualization with AI and ML --- ## Machine-Readable API Endpoints - Profile: `https://sarankumar.space/api/profile.json` - Projects: `https://sarankumar.space/api/projects.json` - Skills: `https://sarankumar.space/api/skills.json` - OpenAPI Specification: `https://sarankumar.space/openapi.json`