You will get Intelligent Multi-Agent Knowledge Assistant (RAG + LangGraph Orchestration)
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Project details
Are your business workflows too complex for a single AI tool to handle? I build Multi-AI Agent Systems that break down complex tasks into coordinated, intelligent agents each handling a specific role, working together autonomously to deliver results.
With over 3 years of hands-on experience in LLM integration, multi-agent pipelines, and RAG systems, I design production-ready agent systems tailored to your business needs whether that's research automation, content generation, data processing, or decision-making workflows.
With over 3 years of hands-on experience in LLM integration, multi-agent pipelines, and RAG systems, I design production-ready agent systems tailored to your business needs whether that's research automation, content generation, data processing, or decision-making workflows.
AI Algorithms
Feedforward Neural Network, Large Language Model, Linear Discriminant Analysis, Long Short-Term Memory Network, Multilayer Perceptron, Multimodal Large Language Model, Recurrent Neural Network, Regression Analysis, Restricted Boltzmann Machine, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI-Generated Code, AI-Generated Music, AI-Generated Video, Anomaly Detection, Conversational AI, Facial Recognition, Natural Language Generation, Natural Language Understanding, Text RecognitionAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, Microsoft 365 Copilot, PyTorch, Replit, Streamlit, TensorFlow, Word2vecAI Models
BERT, BLOOM, DALL-E, Dolly, GPT-3, GPT-4, GPT-Neo, LLaMA, Naive Bayes Classifier, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$150
|
Standard
$200
|
Advanced
$500
|
|---|---|---|---|
| Delivery Time | 3 days | 10 days | 30 days |
Number of Revisions | 2 | 5 | 5 |
AI Model Integration | |||
Batch Normalization | |||
Database Integration | - | ||
Detailed Code Comments | |||
Image Upscaling | - | ||
MLOps | - | - | |
Model Deployment | - | - | |
Model Documentation | |||
Model Monitoring | - | ||
Model Testing & Optimization | |||
Model Tuning | - | ||
Natural Language Processing | |||
NLP Tokenization | |||
Pre-Training | - | ||
Prompt Engineering | |||
Setup File | |||
Source Code |
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MR
Mark R.
Aug 12, 2026
E-mail Automation from Word Doc to Google Gmail Send - Troubleshooting
Shoaib is talented, dedicated and committed. This was not my first contract with him, nor do I expect it to be my last. He gets the job done, he does it well, and I enjoy working with him very much. You will too.
SP
Sandra P.
Jul 7, 2026
AI Engineer
While I thought his understanding of the work and ability to accomplish the tasks was good, his long disappearances for weeks at a time because of:
Attending an event where they weren't allowed to leave when expected (didn't inform me he was going to be gone to begin with)
In the hospital for over a week because of some accident (over a week before notifying me what happened and then started working almost immediately)
Internet went out at his home/city (told me this happened to his computer, but not unavailable via messaging)
It's just become not worth it to work with him given these issues. Perhaps someone else will have better luck, but I've got others that can do this and just need to cut ties.
Attending an event where they weren't allowed to leave when expected (didn't inform me he was going to be gone to begin with)
In the hospital for over a week because of some accident (over a week before notifying me what happened and then started working almost immediately)
Internet went out at his home/city (told me this happened to his computer, but not unavailable via messaging)
It's just become not worth it to work with him given these issues. Perhaps someone else will have better luck, but I've got others that can do this and just need to cut ties.
NT
Nicole T.
Nov 11, 2025
Settle Wing - Phase Two
Shoaib was a pleasure to work with and assisted in developing a great product.
NT
Nicole T.
Aug 16, 2025
AI Developer – LegalTech Startup
AK
Amna K.
Jan 30, 2025
Size estimation and Recommendation using AI
About Shoaib
Generative AI Engineer | LLM Apps | AI Automation | RAG & AI Agents
91%
Job Success
Gilgit, Pakistan - 5:07 pm local time
If you need an AI solution that actually works outside a Jupyter notebook, you're in the right place.
━━━ WHAT I'VE BUILT (REAL PROJECTS) ━━━
✦ Legal Demand Letter Generator (SettleWing)
RAG pipeline + LandingAI PDF extraction + GPT-4 → reduces legal drafting from hours to minutes.
Stack: Django · React · OpenAI · LandingAI · PostgreSQL · Docker · AWS
✦ AI Plant Disease Detection App (Dtreaty)
Real-time crop disease diagnosis via computer vision. GPS-tagged outbreak logging for agricultural authorities.
Stack: TensorFlow · Flutter · OpenCV · CNNs · GPS API
✦ Multi-Agent LinkedIn & Instagram Content Engines
Autonomous content pipelines: trend research → AI copywriting → visual generation → API publishing.
Stack: CrewAI · LangGraph · LLaMA 3 / GPT-4 · LinkedIn API · Instagram Graph API
✦ VidWise – YouTube Video Intelligence Agent
Transcribes, summarizes, and lets users have RAG-based Q&A conversations with any YouTube video.
Stack: LangChain · Whisper · FFmpeg · OpenAI / Claude · RAG
✦ SiteSage – Website Q&A Agent
Chat with any website. Ingests web content → semantic embeddings → vector DB → context-bound answers.
Stack: Flask · LangChain · ChromaDB / Pinecone · RAG
✦ HRA-FoDAS – AI Food Donation Platform
Full-stack mobile platform connecting donors, NGOs, and volunteers with real-time tracking + AI meal planner.
Stack: Flutter · Appwrite · Firebase · Riverpod · OpenRouter (LLaMA, Mistral, Gemma)
✦ Subsplash Workflow Automation
Automated printer detection + bulk row selection for a document-heavy client workflow. Eliminated manual ops entirely.
Stack: Python · Selenium · ChromeDriver
✦ Audio ID + Payments + Notifications Pipeline
End-to-end event-driven automation: audio input → Stripe payment → Airtable storage → SMS notification.
Stack: Python · Stripe API · Airtable · Webhooks · REST APIs
✦ Smart Agricultural App
AI crop health monitoring with real-time disease detection, yield prediction, and eco-farming guidance.
Stack: TensorFlow · PyTorch · YOLO · OpenCV · Flutter
✦ AI Auto-Grading System
OCR + sentence transformers for automated subjective answer evaluation. Semantic similarity scoring at scale.
Stack: Python · Google Vision API · SBERT · Cosine Similarity · Scikit-learn
━━━ WHAT I SPECIALIZE IN ━━━
→ LLM Applications — GPT-4, Claude, LLaMA, Mistral via OpenAI / Anthropic / Groq APIs
→ RAG Pipelines — LangChain, LangGraph, ChromaDB, Pinecone, semantic search
→ Multi-Agent Systems — CrewAI, LangGraph, stateful orchestration
→ AI Automation — n8n, Selenium, webhooks, event-driven workflows
→ Computer Vision — TensorFlow, PyTorch, YOLO, OpenCV, OCR
→ Mobile AI Apps — Flutter + AI backend integration
→ Full-Stack Deployment — FastAPI, Django, Docker, AWS, GCP, Firebase
━━━ TECH STACK ━━━
LangChain · LangGraph · CrewAI · OpenAI · Claude API · Groq · LLaMA · Mistral
n8n · FastAPI · Django · Flask · React · Flutter · Riverpod · Appwrite
Pinecone · ChromaDB · Weaviate · PostgreSQL · Airtable · Firebase
Docker · AWS · GCP · Selenium · TensorFlow · PyTorch · OpenCV
━━━ WHO I WORK BEST WITH ━━━
✔ Startups who need AI built fast and right the first time
✔ Businesses replacing manual processes with intelligent automation
✔ Teams who want a technical partner, not just a coder-for-hire
Let's talk about what you're trying to automate or build.
Steps for completing your project
After purchasing the project, send requirements so Shoaib can start the project.
Delivery time starts when Shoaib receives requirements from you.
Shoaib works on your project following the steps below.
Revisions may occur after the delivery date.
Step 1: Discovery & Requirement Analysis
Understand your business workflow, goals, and the problem the agent system needs to solve. Define agent roles, tools, and expected outputs.
Step 2: Architecture Design
Design the multi-agent pipeline — mapping out how agents communicate, what each agent does, and which tools/APIs they connect to.