You will get a custom AI assistant, multi-agent workflow, or LLM app on Google Cloud
Project details
Looking to build a custom AI assistant, multi-agent workflow, or production-grade LLM application on Google Cloud?
I engineer production-ready AI solutions—from single-model API integrations to complex multi-agent workflows with RAG, custom tool-calling, and serverless cloud architectures.
What you get with this project:
• Multi-Agent & LLM Integration: Custom orchestration using Gemini, OpenAI, Claude, or open-source LLaMA models.
• Model Context Protocol (MCP) & Tools: Connecting AI models to external databases, live APIs, and custom business tools.
• Production Cloud Backend: High-performance Python (FastAPI) backends deployed on Google Cloud Run with scale-to-zero cost efficiency (~$5/mo).
• Data & Knowledge Base: PostgreSQL (Cloud SQL), Firestore, and vector embeddings for context-grounded retrieval.
• Interactive UI & Dashboard: Modern React / Next.js interfaces with streaming responses (SSE/WebSockets).
• Full Handover & Security: Complete repository, Dockerized deployment, environment setup, and encrypted credential storage.
Select a tier to begin or message me with your architecture requirements for a tailored scope.
I engineer production-ready AI solutions—from single-model API integrations to complex multi-agent workflows with RAG, custom tool-calling, and serverless cloud architectures.
What you get with this project:
• Multi-Agent & LLM Integration: Custom orchestration using Gemini, OpenAI, Claude, or open-source LLaMA models.
• Model Context Protocol (MCP) & Tools: Connecting AI models to external databases, live APIs, and custom business tools.
• Production Cloud Backend: High-performance Python (FastAPI) backends deployed on Google Cloud Run with scale-to-zero cost efficiency (~$5/mo).
• Data & Knowledge Base: PostgreSQL (Cloud SQL), Firestore, and vector embeddings for context-grounded retrieval.
• Interactive UI & Dashboard: Modern React / Next.js interfaces with streaming responses (SSE/WebSockets).
• Full Handover & Security: Complete repository, Dockerized deployment, environment setup, and encrypted credential storage.
Select a tier to begin or message me with your architecture requirements for a tailored scope.
AI Algorithms
Autoencoder, Feedforward Neural Network, Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Content Creation, AI Mobile App Development, AI Text-to-Image, AI Text-to-Speech, AI-Generated Code, AI-Generated Video, AIOps, Conversational AI, Facial Recognition, Natural Language Generation, Sentiment AnalysisAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, PyTorch, StreamlitAI Models
AlphaCode, ChatGPT, DALL-E, GPT-4, LLaMA, OpenAI Codex, Stable DiffusionWhat's included
| Service Tiers |
Starter
$120
|
Standard
$350
|
Advanced
$850
|
|---|---|---|---|
| Delivery Time | 2 days | 7 days | 15 days |
Number of Revisions | 1 | 2 | 3 |
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 Mohamed
Full-Stack AI Developer | React | Node.js | SaaS | Python
Dubai, United Arab Emirates - 5:20 pm local time
Founder of Bagback Digital Solutions — an AI product studio and startup enablement company. Co-founder of Elitk. Over the past 3 years I've architected and shipped 8+ production systems: enterprise AI operations platforms, multi-module SaaS products, bilingual lead-generation websites, AI-powered productivity tools, and multi-vendor e-commerce platforms.
——— WHAT I BUILD ———
AI SaaS & Multi-Agent Systems
Multi-tenant SaaS platforms with autonomous AI workflows, multi-agent orchestration via Genkit and Vertex AI, real-time WebSocket event buses, and full RBAC. I've delivered a 10-module AI marketing OS and an enterprise operations platform with 4 autonomous AI Directors covering Marketing, Finance, HR, and Strategy.
Bilingual Next.js Platforms (Arabic RTL + English LTR)
Parallel-language web apps with correct RTL layout, Arabic typography, separate bilingual SEO metadata, JSON-LD structured data, Firebase CMS, and WhatsApp conversion flows — optimized for UAE and MENA market requirements.
Full-Stack AI Integrations
React or Next.js frontends + Node.js/Express or FastAPI backends + Gemini or Vertex AI + Firestore or PostgreSQL. Every layer typed in TypeScript, deployed, and documented — not prototyped.
——— SELECTED WORK ———
Elitk — 10-module AI marketing operating system with 6 social platform integrations (Facebook, Instagram, TikTok, LinkedIn, Twitter/X, YouTube), real-time analytics, WebSocket event bus, and a 13-tab SuperAdmin panel. Built on React 18, Node.js/Express 5, PostgreSQL, and Gemini AI.
Bagback Ops — Enterprise AI operations platform with 4 autonomous AI Directors, multi-tenant multi-industry architecture, PWA offline capability, and full bilingual parity. Built on Next.js 15, Firebase Cloud Functions v2, Genkit, and Vertex AI.
Bagback AI Workspace — 2,770+ curated bilingual prompts plus MCP integration hub. FastAPI backend on GCP Cloud Run with scale-to-zero architecture. Includes live AI workbench with prompt testing, auto-optimization, and encrypted credential storage.
Laforma — Bilingual UAE lead-generation platform with Firebase Firestore CMS managing 12 content collections, WhatsApp-native conversion flows, JSON-LD structured data, and static-export performance on Firebase Hosting.
——— TECH STACK ———
Next.js 14/15/16 · React 18/19 · TypeScript · Firebase (Auth, Firestore, Hosting, Functions v2) · Genkit · Vertex AI · Gemini API · Node.js/Express · FastAPI · PostgreSQL · Drizzle ORM · GCP Cloud Run · Tailwind CSS · Framer Motion · Docker · Zustand · PWA
I communicate in English and Arabic. Every system I deliver is production-grade and deployed — not a proof of concept.
Steps for completing your project
After purchasing the project, send requirements so Mohamed can start the project.
Delivery time starts when Mohamed receives requirements from you.
Mohamed works on your project following the steps below.
Revisions may occur after the delivery date.
Architecture & Model Selection
Review your user workflows, choose optimal LLM models (cost vs speed), and plan system data flow.
I Engine & Prompt Engineering
evelop FastAPI backend, configure tool-calling/MCP, and build robust context-grounded prompt logic.