Muhammad Ghulam J.

AI agents, RAG systems, and AI chatbots that still work 6 months after launch. That is the whole job, and it is harder than the demo makes it look. I build them on LangGraph, LangChain, n8n, Python, and FastAPI, and every number on this profile was measured against a baseline before the build and a scored test set after it.

A US company runs its daily operations on a multi-agent platform I built, now past 1,000 hours in production. I am a 2x Claude Certified Architect (874 on Anthropic's proctored Professional exam, pass mark 720), plus AWS, Azure, and GCP professional certificates and 6+ years of ML foundations as a Top 100 Global Kaggle Master. Every hour on my contracts is delivered by me.

Here is how I keep the percentages below honest: I measure the starting point, build a scored test set from your real data, and track the same metric after launch. Most builds below were delivered under NDA, so instead of logos, I offer this: on our first call, I open the evaluation dashboard from a comparable build and show you the measurement behind any figure here.

𝐏𝐑𝐎𝐎𝐅:

1. Enterprise RAG: search time down 70%, retrieval precision up 75%, 8,000+ live queries daily.
   Skill set: Retrieval-Augmented Generation, LangGraph, LangChain, Pinecone, hybrid search
2. Legal LLM, on-premises: Gemma 3 27B fine-tuned on 400K+ documents, 91% citation accuracy, zero hallucinated citations, 60% lower inference cost.
   Skill set: LLM fine-tuning, Gemma 3, QLoRA, DPO, vLLM, on-premises deployment
3. Voice AI: 80%+ of tier-1 calls handled end-to-end, under 1-second response, handle time down 45%.
   Skill set: Voice AI, LiveKit, Deepgram, ElevenLabs, Whisper, Retell, Vapi
4. HIPAA clinical AI: grounded in the hospital's own clinical records, with human review before anything enters the chart. 91% factual accuracy, intake time down 27%, manual documentation down 48%.
   Skill set: RAG, Claude, PHI handling, AI guardrails, LangSmith, healthcare AI
5. Revenue agents: a multi-agent system that qualifies leads, runs follow-ups, and keeps the CRM current on its own. $340K pipeline in the first 6 months, 1.8x more qualified leads, 48% less manual sales ops, 900+ automated triggers firing daily.
   Skill set: Multi-agent orchestration, CrewAI, n8n, AI automation, CRM automation
6. Autonomous support: 1 system across 7 channels that hands off to a human the moment confidence drops. 61% of requests resolved end to end, average response 44% faster, engagement up 23%.
   Skill set: Conversational AI, AI chatbot, OpenAI API, n8n, intent routing