You will get text Build Your AI-Powered MVP — Full Product, Idea to Deployment
Project details
I build complete AI-powered products — backend, frontend, AI pipeline, database, deployment. Not prototypes. Not notebooks. Shipped software serving real users.
I've solo-built 3 AI products to production:
→ AI wellness platform — 10K+ users, 50K+ conversations, 3 generative models, real-time video avatars
→ AI music platform — 3 production models (video, song synthesis, instrumentals), 50+ daily users
→ Professional matchmaking MVP — shipped solo in 5 months on AWS
My process: discovery call → architecture spec you approve → weekly build demos → deployed product with full docs and handoff. No surprises.
Need a technical co-founder's output without equity cost? That's exactly what this is.
Stack: Python, FastAPI, PyTorch, Hugging Face, LangChain, Next.js, PostgreSQL, Redis, Docker, AWS, Modal.
I've solo-built 3 AI products to production:
→ AI wellness platform — 10K+ users, 50K+ conversations, 3 generative models, real-time video avatars
→ AI music platform — 3 production models (video, song synthesis, instrumentals), 50+ daily users
→ Professional matchmaking MVP — shipped solo in 5 months on AWS
My process: discovery call → architecture spec you approve → weekly build demos → deployed product with full docs and handoff. No surprises.
Need a technical co-founder's output without equity cost? That's exactly what this is.
Stack: Python, FastAPI, PyTorch, Hugging Face, LangChain, Next.js, PostgreSQL, Redis, Docker, AWS, Modal.
AI Algorithms
Autoencoder, Convolutional Neural Network, Generative Adversarial Network, Large Language Model, Multimodal Large Language Model, Transformer Model, Variational AutoencoderAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, AI-Generated Code, AI-Generated Music, AI-Generated Video, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, Gradio, Hugging Face, PyTorch, Streamlit, TensorFlowAI Models
BERT, ChatGPT, GPT-3, GPT-4, LLaMA, Stable Diffusion, WhisperWhat's included
| Service Tiers |
Starter
$800
|
Standard
$2,000
|
Advanced
$4,500
|
|---|---|---|---|
| Delivery Time | 14 days | 30 days | 45 days |
Number of Revisions | 2 | 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 |
Optional add-ons
You can add these on the next page.
Stripe Payment Integration
(+ 3 Days)
+$300
Admin Dashboard
(+ 5 Days)
+$500
Post-Launch Support — 2 Weeks
+$400Frequently asked questions
About Ahmed
ML Engineer | GenAI & LLM Deployment | 10K+ Users in Production
Cairo, Egypt - 6:32 pm local time
production systems, not just Jupyter notebooks.
I build AI systems that serve real users at scale. My current platforms handle
10K+ users and 50K+ conversations with 99.9% uptime.
WHAT I BUILD:
→ AI Chatbots & RAG Systems
Custom chatbots trained on YOUR data (documents, PDFs, databases, websites).
Your customers get accurate, sourced answers instantly.
Tech: LangChain, ChromaDB/Pinecone, OpenAI/Claude/Llama, FastAPI
→ LLM Integration & Deployment
Take any AI model from prototype to production — with proper monitoring,
safety filters, cost optimization, and auto-scaling.
Tech: PyTorch, Hugging Face, Modal, AWS, Docker
→ Full AI Product MVPs
I've built complete AI products as sole engineer — from database design
to production deployment. If you need a technical co-founder who executes,
I'm your person.
WHAT I'VE SHIPPED (not side projects — live production systems):
• AdviceBuddy.ai — 10K+ users, 50K+ conversations, Llama 3.1-8B with
real-time video avatars and 12 voice configurations
• SongLabAI — 3 generative AI models in production (video, music, instrumentals),
50+ daily users
• Connectyed — Full matchmaking platform MVP, shipped solo in 5 months
WHY CLIENTS CHOOSE ME:
✓ I deploy to production, not just prototype
✓ I optimize inference costs (saved 60-90% on GPU spending across 5 models)
✓ I handle the full stack — model, backend, frontend, deployment
✓ Clear communication, async-friendly, weekly progress demos
Stack: Python, PyTorch, Hugging Face, LangChain, FastAPI, Docker, AWS,
Modal, PostgreSQL, Redis, ChromaDB, Next.js, Streamlit
Let's talk about your project → send me a message with what you're building
and I'll respond within a few hours with an honest assessment of whether
AI is the right solution and how I'd approach it.
Steps for completing your project
After purchasing the project, send requirements so Ahmed can start the project.
Delivery time starts when Ahmed receives requirements from you.
Ahmed works on your project following the steps below.
Revisions may occur after the delivery date.
Discovery & Technical Scoping
30-minute call to understand your product, users, and constraints. I deliver a system architecture document with database schema, API endpoints, and tech stack recommendation within 48 hours.
Architecture Approval & Environment Setup
You review and approve the architecture. I set up the repository, cloud infrastructure, CI/CD pipeline, and development environment. Nothing gets built until you sign off on the plan.