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MU

MUHAMMAD USMAN

Tier 2 (Warm)Unclaimed Profile

@muhammadusmanray-ops

AI & Backend Developer | Building Agentic AI Systems Supabase • Firebase • Vercel • OpenAI • System Design Passionate about scalable architectures & intel

sylani ISLAMABAD 4 stars On GitHub since 2025

Analyzed 5d ago

Repos Analyzed

8

With LLM Usage

2

Total Call Sites

4

LLM Providers

1

Stack Complexity
basic
18/100
AI Providers
1
Frameworks
1
Architecture Overview

LLM Providers

Google

Models

gemini-2.5-pro

Frameworks

LangChain
Profile README
#  Muhammad Usman Ray | Senior AI & Machine Learning Engineer
# 🧠 Architecting the Future with LLMs, Gemini APIs & Agentic Workflows 🌐


  


---

### 👤 About Me
Expert **Applied AI Engineer** specializing in the frontier of **Generative AI**. I build complex multi-agent systems using **LangGraph** and high-performance RAG pipelines leveraging **Gemini Pro** & **GPT-4**. My work bridges the gap between raw Machine Learning models & production-grade autonomous agents.

- 🛠️ **Current Focus:** Building the next-gen **Atlas DS** Agentic Platform.
- 🧪 **Expertise:** LLM Fine-tuning, RAG Architectures, Vector Databases (Pinecone/Supabase), & Computer Vision.
- ⚡ **Frameworks:** LangChain, LangGraph, CrewAI, AutoGen, TensorFlow, Scikit-Learn.
- 📈 **Innovation:** Implementing Zero-cost AI Fallbacks & custom MCP servers for intelligent tool use.

---

### 🛠️ Strategic Technology Stack

| Category | Skills & Technology Store |
| :--- | :--- |
| **🧠 Large Language Models** |    |
| **🤖 Agentic Frameworks** |    |
| **📊 ML & Data Science** |    |
| **💻 Backend & Cloud** |    |

---

### 🏆 Featured AI Project Portfolio


  
    
       🤖 Atlas DS - Agentic AI Engine
       Advanced orchestration platform using LangGraph for autonomous task execution. Includes custom MCP servers and intelligent tool integration.
       Explore System →
    
    
       
    
  
  
    
       💬 Medical AI Chatbot (CrewAI)
       Multi-agent medical consultancy system using Gemini Pro. Capabl...
View full profile on GitHub
Interactive Cost Calculator

Estimate costs using published model pricing and your own volume inputs.

Model

Daily API Calls

1,000
10100K

Avg Tokens per Request

1,000
10010,000

gemini-2.5-pro pricing

Input: $1.25/1M tokens  ·  Output: $10/1M tokens

These estimates use published model pricing. Actual costs depend on your call volume, prompt length, and response size.

Repositories with LLM Usage (2)

ATLAS-MEDICAL-AI

AI Medical Assistant

10/100 basic
Googlegemini-2.5-pro
2 call sites0 files checked1

Other repos checked (6)

atlas-clawMusmanATLAS-DSMUHAMMAD-USMANUNIVERSITY-LABmuhammadusmanray-ops
CHURN-AI-ml-1-
18/100 basic
Googlegemini-2.5-proLangChain
2 call sites0 files checked