Nataraj Angappan

Cisco ISE & Wireless Technical Lead · Network Security · AI Automation

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🚀 "I apply RAG, agents and small language models to real network-operations problems — with answers grounded in evidence and a human in the loop."

👋 Who I Am I'm Nataraj Angappan — a Cisco ISE and Wireless Technical Lead at Cognizant, working across enterprise network security, NAC, routing and switching, and Catalyst wireless. I build AI tooling that makes that work faster and more explainable: RAG assistants that explain authentication flows, agent workflows that keep a human approving every consequential change, and a small language model that diagnoses Wi-Fi RF problems across 2.4, 5 and 6 GHz. My bias is toward grounded answers, evidence trails and vendor-neutral design over flashy demos.

⚡ At a Glance name: Nataraj Angappan role: Cisco ISE & Wireless Tech Lead company: Cognizant location: Coimbatore, India focus: NAC · Wireless · RF · AI Automation languages: Python · TypeScript building: RF Root Cause SLM (QLoRA) ISE Chatbot, Agentic-AI, BGP Automation. repos: 42 public

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🔭 Currently Building & Exploring

🛠️ Building 📶 RF root-cause SLM — Qwen2.5-1.5B, QLoRA, RAG for regulatory facts 🔑 Cisco ISE / RADIUS flow assistants with RAG 🛰️ Catalyst 9800 DR-readiness and failover automation 🤖 Multi-agent IT-ops workflows with human approval gates

🌱 Exploring 🕸️ Graph RAG vs vector RAG on multi-hop questions 🧠 Small-model fine-tuning and offline teacher–student distillation 🔌 MCP and n8n agent workflows 💻 Local LLMs with Ollama on modest hardware

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🧰 Tech Stack

🧠 Languages & Core
⚙️ Backend & Frontend
🤖 AI & Automation
🌐 Networking & Security

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📌 Featured Projects

Project	What it does
📶 SLM — Wi-Fi RF issues	Diagnoses 2.4 / 5 / 6 GHz RF problems and returns a root cause with a supporting evidence chain. Vendor-neutral schema, QLoRA fine-tune, RAG for regulatory facts, FastAPI + React, and an ESP32 hardware probe.
🔑 ISE Flow Assistant	A RAG chatbot that explains Cisco ISE and RADIUS/AAA flows — and draws them.
🛰️ Catalyst 9800 DR Readiness	Scores wireless disaster-recovery readiness from controller CLI state and plays an operator-gated site failover, on pyATS/unicon mocks.
🧪 netsim lab	Simulates Cisco ISE / NAC, wireless and Catalyst Center scenarios on an 8 GB laptop, no CML required.
🕸️ Knowledge Graph RAG	Measures how much required evidence Graph RAG surfaces versus vector-only RAG on multi-hop questions.
🧰 IT Ops Assistant	Multi-agent IT-operations command center with human-in-the-loop manager approval.

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📊 GitHub Stats

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🧭 Principles I Build By

• Ground it or don't say it. Numbers and policy claims come from retrieval with a citation, not from a model's memory.
• Show the evidence. An answer without a trail isn't usable in operations.
• Keep a human in the loop for anything that changes a production network.
• Vendor-neutral where it counts — normalise at the boundary instead of retraining or rewriting.

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🤝 Let's Connect

Open to conversations about wireless, NAC and practical AI for network operations.