You will get a custom AI Agent, RAG chatbot, or LangGraph workflow
Rising Talent
Project details
Looking for a custom AI agent that can automate your business, answer customer queries, process documents, or integrate with your existing tools?
You're in the right place.
I build production-ready AI agents using LangChain, LangGraph, OpenAI, RAG, MCP, and modern LLM technologies. Whether you need a chatbot, a multi-agent workflow, a document Q&A assistant, or an AI-powered business automation system, I can deliver a scalable and reliable solution tailored to your requirements.
My services include:
✅ Custom AI Agents
✅ AI Chatbots
✅ RAG (Retrieval-Augmented Generation)
✅ Multi-Agent Systems
✅ OpenAI, Claude, Gemini & Llama Integration
✅ FastAPI & REST API Development
✅ n8n Automation Workflows
✅ Vector Databases (Pinecone, Qdrant, ChromaDB)
✅ Database & API Integration
✅ Deployment & Source Code
Why work with me?
✔ Clean and scalable code
✔ Fast communication
✔ On-time delivery
✔ Well-documented solutions
✔ Long-term support
Let's build an AI solution that saves time, improves productivity, and helps your business grow.
You're in the right place.
I build production-ready AI agents using LangChain, LangGraph, OpenAI, RAG, MCP, and modern LLM technologies. Whether you need a chatbot, a multi-agent workflow, a document Q&A assistant, or an AI-powered business automation system, I can deliver a scalable and reliable solution tailored to your requirements.
My services include:
✅ Custom AI Agents
✅ AI Chatbots
✅ RAG (Retrieval-Augmented Generation)
✅ Multi-Agent Systems
✅ OpenAI, Claude, Gemini & Llama Integration
✅ FastAPI & REST API Development
✅ n8n Automation Workflows
✅ Vector Databases (Pinecone, Qdrant, ChromaDB)
✅ Database & API Integration
✅ Deployment & Source Code
Why work with me?
✔ Clean and scalable code
✔ Fast communication
✔ On-time delivery
✔ Well-documented solutions
✔ Long-term support
Let's build an AI solution that saves time, improves productivity, and helps your business grow.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI-Enhanced Classification, AI-Generated Code, Automatic Speech Recognition, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Hugging Face, NVIDIA AI PlatformAI Models
AlphaCode, ChatGPT, DALL-E, Dolly, GPT-3, GPT-4, GPT-J, LLaMA, Naive Bayes Classifier, OpenAI Codex, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$130
|
Standard
$350
|
Advanced
$750
|
|---|---|---|---|
| Delivery Time | 7 days | 7 days | 14 days |
Number of Revisions | 3 | 3 | 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 |
Frequently asked questions
About Shan
AI Agent Engineer | Voice AI | AI Chatbots | RAG Systems | Multi-Agent
Lahore, Pakistan - 7:06 pm local time
𝗬𝗼𝘂 𝗻𝗲𝗲𝗱 𝗔𝗜 𝘁𝗵𝗮𝘁 𝘀𝘂𝗿𝘃𝗶𝘃𝗲𝘀 𝗿𝗲𝗮𝗹 𝘂𝘀𝗲𝗿𝘀 — 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗮 𝗰𝗹𝗲𝗮𝗻 𝗱𝗲𝗺𝗼.
Two years ago I shipped my first Voice AI agent. Flawless in testing. Then a caller with a heavy accent asked a question while their dog barked in the background — and the whole thing fell apart.
That day taught me the real ratio: the demo is 10% of the work. The other 90% is bad audio, CRM timeouts, users saying "um" fourteen times, and edge cases nobody warns you about.
I only build AI that survives that 90% now.
𝗪𝗵𝗮𝘁 𝗜'𝘃𝗲 𝘀𝗵𝗶𝗽𝗽𝗲𝗱
𝗤𝗮𝗹𝗶𝗳𝗔𝗜 — Handles 40+ real estate calls daily, live leads not test calls, 92% intent accuracy across thousands of conversations. VAPI + ElevenLabs voice, GoHighLevel CRM sync, Google Calendar booking. Qualifies buyers, handles objections, hands off to humans without losing context.
𝗣𝗮𝗽𝘆𝗿𝘂𝘀 — Answers research questions across 15,000+ academic papers using hierarchical chunking, hybrid search (pgvector), and Cohere reranking. It says "I don't know" when confidence is low — which is why researchers actually trust it.
𝗘𝗮𝘀𝘁𝗹𝗮𝘄 — Searches 300,000+ Pakistani court judgments via Elasticsearch filtering + semantic search. FastAPI backend serving 200+ concurrent users. Lawyers use it every morning.
𝗔𝗜 𝗙𝗿𝗮𝗻𝗸 — Generates legal documents with jurisdiction-aware retrieval and proper statute citations. 700+ documents created. React + Python + pgvector for precedent matching.
𝗦𝘁𝗮𝘆𝗦𝗾𝘂𝗶𝗿𝗲 — Runs hotel reception calls: bookings, availability, guest requests. Retell voice + n8n automation, integrated directly with property management systems.
𝗛𝗼𝘄 𝗜 𝘄𝗼𝗿𝗸
I build Voice AI agents, RAG systems, and AI MVPs — for teams past the "exploring AI" stage who need something actually deployed. If you're still deciding whether AI is worth it, I'll tell you honestly if it isn't.
Most projects run $2K–25K over 2–6 weeks. I don't disappear mid-build, I document everything, and I build for handoff — so you're not stuck depending on me forever.
𝗧𝗲𝗰𝗵 𝘀𝘁𝗮𝗰𝗸
𝗩𝗼𝗶𝗰𝗲 𝗔𝗜: VAPI, Retell, Twilio, Bland, ElevenLabs, Whisper, OpenAI TTS, Deepgram
𝗥𝗔𝗚 & 𝗟𝗟𝗠𝘀: LangChain, LangGraph, LlamaIndex, OpenAI, Claude, Gemini, Cohere, pgvector, Qdrant, Pinecone, Elasticsearch
𝗕𝗮𝗰𝗸𝗲𝗻𝗱: Python, FastAPI, Node.js, TypeScript, PostgreSQL, Redis, Supabase
𝗙𝗿𝗼𝗻𝘁𝗲𝗻𝗱: React, Next.js, Tailwind CSS
𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: n8n, Make, Zapier, GoHighLevel, HubSpot, Stripe, WhatsApp Business API
𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁: AWS, GCP, Vercel, Railway, Docker
𝗪𝗵𝗮𝘁 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 𝘀𝗮𝘆
"Shan is excellent to work with. Fast, thorough, quick to accept feedback. His team is great — we've loved building multiple software solutions together. Fantastic Upwork contractor."
Tell me what you're building, and I'll send you a FREE technical architecture outline with the recommended AI stack, workflow, and implementation approach before you commit. If we're a good fit, I'll help you build an AI system that works reliably in production—not just in a demo.
Steps for completing your project
After purchasing the project, send requirements so Shan can start the project.
Delivery time starts when Shan receives requirements from you.
Shan works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis
I'll review your project requirements, business goals, and recommend the best AI architecture.
Development
I'll build your AI agent, integrate APIs, implement RAG or automation workflows, and provide regular progress updates.