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Available for Enterprise Engagements

AI Engineer · Automation Architect · Systems Builder

Building AI Systems That Compound
Business Value

I design and deploy enterprise-grade AI infrastructure — from intelligent automation pipelines to multi-agent orchestration systems — that eliminate operational bottlenecks, accelerate decision cycles, and create compounding leverage for high-growth companies.

Currently building at
Orange Business
NovaMind AI
FutArt
Cairo, Egypt
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0
Years Engineering AI Systems
0
Enterprise Projects Delivered
0
AI Products Built & Shipped
0
Startups Founded
About

Engineering AI at the
Intersection of Scale
and Intelligence

I'm Mario Shady — a Data & AI Engineer designing enterprise AI systems at Orange Business in Cairo. My work sits at the intersection of data engineering, AI systems design, and product strategy.

Every system I build is engineered to compound in value over time: eliminating operational overhead, accelerating decision cycles, and creating AI-native workflows that scale without proportional headcount increases.

Businesses that embed AI into their operations as a capability layer — not just a point solution — will have an insurmountable advantage inside two years. I help the ones serious about that transition get there first.

Data Engineer — Orange Business AI & Data Department · Enterprise-scale data infrastructure
🧠
Founder — NovaMind AI Enterprise automation & AI systems · PMWA & MAAG products
🔭
Founder — FutArt Building the AI operating layer for smart glasses ecosystems
🏗️
Systems Architect — Full Stack AI Python · Cloud · LLMs · Agentic workflows · Distributed systems
MS
Mario Shady
Data & AI Engineer · Founder
5+
Years Experience
20+
Projects Delivered
3
AI Products Built
2
Startups Founded
Core Focus Areas
AI Engineering Data Platforms Automation Cloud Arch LLM Systems
Available for projects · Cairo, Egypt
Services

What I Build
for Your Business

Every engagement is scoped to deliver measurable operational impact — not just technology delivery. Here's where I drive the most value.

Enterprise AI Integration
Embed production-grade AI models directly into your existing systems. From CRMs and ERPs to custom internal tools — I build the connective tissue that makes AI actionable across your entire operation.
OpenAI Claude API LangChain REST/GraphQL
AI Automation Systems
Design and deploy end-to-end automation architectures that replace manual workflows with intelligent pipelines. Trigger-based, event-driven systems that run 24/7 without oversight.
Python N8N Zapier Custom Pipelines
AI Agents & Copilots
Build autonomous AI agents and intelligent copilots tailored to your business logic. Multi-agent orchestration systems that reason, plan, and execute complex multi-step workflows independently.
Multi-Agent RAG Systems Vector DBs LLM Orchestration
Data Engineering & Platforms
Architect modern data platforms from the ground up or modernize legacy systems. ETL/ELT pipelines, data lakes, real-time streaming, and analytics infrastructure that scales with your growth.
Snowflake Databricks Spark dbt
Cloud Architecture & Infrastructure
Design cloud-native architectures on AWS and Azure that are resilient, cost-efficient, and built for AI workloads. Kubernetes orchestration, serverless patterns, and full CI/CD automation.
AWS Azure Kubernetes Docker
Business Intelligence & Analytics
Transform raw data into executive-grade intelligence dashboards and reporting systems. Real-time KPI tracking, predictive analytics, and AI-powered insight surfaces that drive strategic decisions.
Power BI SQL Python AI Dashboards
AI SaaS Development
Build AI-native SaaS products from idea to production. Full-stack architecture, API-first design, multi-tenant systems, and scalable backend infrastructure for AI-powered applications that serve thousands.
Next.js FastAPI PostgreSQL Redis
Business Process Automation
Identify, map, and automate your most expensive manual processes. From lead handling and onboarding flows to invoice processing and support triage — I build systems that run without human intervention.
Workflow AI WhatsApp API CRM Sync Auto-routing
AI Strategy & Consulting
Cut through AI hype and build a real roadmap. I audit your current operations, identify the highest-ROI automation opportunities, and define an AI adoption strategy that's executable and measurable.
AI Audit Roadmapping ROI Modeling Tech Strategy
Selected Work

Systems Built,
Problems Solved

All Projects
# Enterprise Data Platform — Orange Business class DataPlatformOrchestrator: def ingest_stream(self, source): pipeline = SparkPipeline(source) return pipeline.transform().sink( target="snowflake.analytics" ) def ai_classify(self, batch): # 2.4M records/hr · 99.7% accuracy return self.model.predict_batch(batch)
Data Engineering 2024

Enterprise Data Platform Modernization

Redesigned a legacy reporting infrastructure into a cloud-native, real-time data platform serving the Orange Business Data & AI department. Built distributed ingestion pipelines, Snowflake-based warehouse, and AI classification layers.

⚡ Reduced data processing latency from 6 hours to 4 minutes
SparkSnowflakeAzurePythonKafkadbt
// PMWA — WhatsApp AI Automation Engine const agent = new PMWAAgent({ triggers: ['lead_capture', 'follow_up'], ai_model: 'gpt-4o', crm_sync: 'hubspot', }); // Handles 1,200+ messages/day autonomously agent.onMessage(async (msg) => { const intent = await agent.classify(msg); return agent.respond(intent); });
AI Automation · NovaMind AI 2024

PMWA — Product Management WhatsApp Automator

Built a fully autonomous WhatsApp AI system that handles lead capture, qualification, follow-up sequences, and CRM synchronization. Zero human intervention required for standard lead flows.

⚡ 80% reduction in manual sales communication overhead
OpenAIWhatsApp APINode.jsPostgreSQLLangChain
# AI Analytics Intelligence Layer def generate_insight(df, query): context = build_context(df.describe()) prompt = f""" Analyze this data and answer: {query} Context: {context} Format: executive_brief """ return llm.invoke(prompt) # Serving 47 dashboards · 12 departments
AI Analytics 2024

AI-Powered Executive Intelligence Dashboard

Built an AI analytics layer on top of existing BI infrastructure, enabling natural language querying of enterprise data, automated anomaly detection, and AI-generated executive briefings delivered daily.

⚡ Eliminated 15+ hours of manual reporting per week per department
PythonFastAPIOpenAIReactSnowflake
// MAAG — Mobile App Automatic Generator interface AppSpec { name: string; screens: Screen[]; features: Feature[]; } async function generateApp(spec: AppSpec) { const code = await AICodeGen(spec); const app = await FlutterBuilder(code); // Full Flutter app in 4 minutes return app.compile({ platforms: ['ios','android'] }); }
AI SaaS · NovaMind AI 2025

MAAG — Mobile App Automatic Generator

An AI-powered system that generates fully functional Flutter mobile applications from natural language specifications. Handles UI generation, business logic, backend integration, and app store readiness automatically.

⚡ Reduces app development time from 3 months to under 4 hours
FlutterClaude APIPythonFastAPIFirebase
Technology

The Technical Arsenal

A battle-tested stack built for enterprise-scale AI systems, distributed data platforms, and production-grade automation.

AI & Machine Learning
OpenAI GPT-4o
Claude (Anthropic)
LangChain
LlamaIndex
RAG Systems
Vector Databases
Multi-Agent Orchestration
Prompt Engineering
Fine-tuning
AI Voice Systems
Data Engineering
Apache Spark
Snowflake
Databricks
Apache Kafka
dbt
Apache Airflow
Data Lakes
ETL/ELT Pipelines
PostgreSQL
Redis
Cloud & DevOps
AWS
Microsoft Azure
Kubernetes
Docker
GitHub Actions CI/CD
Terraform
Serverless
Monitoring & Observability
Backend & Systems
Python
Java
Node.js
FastAPI
C++
REST / GraphQL APIs
Microservices
Event-Driven Architecture
Frontend & Mobile
React / Next.js
TypeScript
TailwindCSS
Flutter
Framer Motion
Ventures

Building Beyond
The Next Horizon

Two companies in motion. One long-term vision: an AI operating layer that fundamentally changes how humans interact with technology.

NovaMind AI builds enterprise-grade AI automation systems, SaaS products, and high-ticket AI solutions for businesses ready to operate at the next level. Every product is designed to eliminate manual work at scale and compound operational efficiency over time.

PMWA Product Management WhatsApp Automator — autonomous lead handling & CRM sync at scale
MAAG Mobile App Automatic Generator — AI-native Flutter app generation from natural language specs

FutArt is building the intelligence layer that will sit between humans and their wearable technology. Starting with Meta Ray-Ban smart glasses, the vision extends across every major wearable ecosystem — creating a persistent, context-aware AI presence that operates as a true cognitive extension.

Vision Behavior modeling & digital twin — a personal AI that knows your patterns, context, and goals
Layer Cross-platform AI OS for smart glasses — unified intelligence across Meta, Apple, Samsung, Google
Long-Term Vision

The AI Operating System
for Smart Glasses

Every system I build today is infrastructure for tomorrow. The data pipelines, AI agents, automation frameworks, and product architectures I'm designing now form the foundation of an AI operating layer that will redefine human-computer interaction across the next decade of wearable technology.

Meta Ray-Ban Apple Vision Samsung AR Google Glasses Motorola LG Wearables
Fit

Who I Work
Best With

I take on a small number of engagements per quarter. Here's who gets the most out of working with me.

Ops Leaders Drowning in Manual Work
Your team is spending 40%+ of their time on work that should be automated. Reports, follow-ups, data wrangling, triage. You know it's a problem — you haven't had time to solve it.
→ I map it, scope it, and build the system that eliminates it.
🧠
CTOs Who Need AI in Their Stack Now
You've been watching AI mature and now it's time to move. You need someone who can audit your architecture, identify the highest-leverage integration points, and build it production-ready.
→ I architect and deliver — no hand-holding required.
🚀
Founders Building AI-Native Products
You have a product idea with AI at its core — but you need the technical foundation to be right from day one. Scalable backend, AI orchestration, multi-tenant architecture.
→ I build the infrastructure your idea actually needs.
📊
Companies Sitting on Unused Data
You have data. It's scattered, underused, and generating reports nobody reads. You need a platform that turns it into operational intelligence that drives actual decisions.
→ I build the data layer and the AI layer on top of it.
Not a good fit if you're looking for:
Simple no-code automations One-off scripts with no strategy Hourly freelance work "Explore what AI can do" sessions MVPs with no production path
Process

How Every Engagement
Actually Runs

No black boxes. No scope creep. Every project follows the same five-phase structure — from problem diagnosis to deployed, monitored system.

01
Week 1
Audit & Bottleneck Mapping
I map your current workflows end-to-end. Every manual step, every handoff, every system involved. The goal is to identify the 2–3 highest-ROI automation opportunities — not build a list of nice-to-haves.
Workflow Analysis ROI Estimation Feasibility Score
02
Week 1–2
Architecture Design
I design the technical architecture before a single line of code is written. Data flows, integration points, AI model selection, deployment targets, and failure modes — all documented and reviewed with you.
System Design Tech Selection Integration Mapping
03
Week 2–6
Build & Iterate
I build in two-week sprints with working demos at each checkpoint. You see progress continuously — not a big reveal at the end. If priorities shift, the architecture accommodates it.
Sprint Development Bi-weekly Demos Test Coverage
04
Final Week
Production Deployment
Zero-downtime deployment to your cloud environment. Full CI/CD pipeline, monitoring, alerting, and documentation. Your team gets a handoff session — not a GitHub link and a good luck.
CI/CD Pipeline Monitoring Team Handoff
05
Ongoing
Monitor & Optimize
30-day post-launch monitoring included on every project. I track system performance, catch edge cases in production, and optimize based on real usage data — not test assumptions.
Performance Tracking Edge Case Resolution Continuous Improvement
Under the Hood

Technical Depth
Across Every Layer

Not just "AI integration" — real engineering across the full stack. Here's where the complexity actually lives.

AI Orchestration
Multi-Agent Pipeline Design
Designing systems where multiple AI agents collaborate — planner, executor, validator, and memory manager — with deterministic fallback paths when LLM output variance exceeds tolerance thresholds.
⚡ Used in production: 40 concurrent document workflows
Data Engineering
Streaming vs. Batch at Scale
Choosing between Kafka streaming and micro-batch processing based on latency SLAs, cost constraints, and downstream query patterns. Most teams get this wrong and pay 3x in infrastructure cost.
⚡ Reduced processing latency: 6 hours → 4 minutes
LLM Systems
Context Management at Scale
Maintaining coherent conversation state across long-running sessions — Redis-backed context compression, sliding window strategies, and intelligent summarization to stay within token budgets without losing information.
⚡ 1,200+ concurrent WhatsApp conversations managed
Code Generation
Deterministic AI Code Synthesis
Template-guided generation with a scaffolding layer that enforces architectural consistency. Human-in-the-loop review gate before compilation prevents LLM output variance from reaching production.
⚡ Full Flutter app generated in under 4 hours
Analytics AI
Natural Language → SQL with Schema Injection
Schema-aware context injection enables accurate NL-to-SQL translation across 200+ table databases. Statistical baseline anomaly detection feeds LLM explanation generation for exec-ready briefings.
⚡ 47 dashboards serving 12 enterprise departments
Infrastructure
AI Workload Kubernetes Orchestration
GPU-aware pod scheduling, model caching strategies, horizontal scaling triggers based on inference latency (not just CPU), and cost-optimized spot instance usage for batch inference pipelines.
⚡ 99.7% uptime across enterprise deployments
Social Proof

What Clients
Are Saying

From CTOs to Founders — enterprise leaders on working with Mario Shady.

"Mario inherited a reporting pipeline that took 6 hours to run and handed us back a system that finishes in under 4 minutes. He mapped the bottlenecks in the first week, had a proof of concept on Spark by week two, and pushed to production in 38 days. Measured ROI inside the first month."

AK
Ahmed Karim
CTO · DataNile Solutions

"We had a WhatsApp sales flow that required three people to manage manually. Mario built an autonomous system that now handles 1,200+ messages a day — lead capture, qualification, follow-up, CRM sync. We reassigned those three people to actual sales. The system paid for itself in the first month."

HF
Hossam Farouk
CEO · Nile Commerce Group

"I asked for a reporting dashboard. What I got was an AI layer that queries our data warehouse in plain English, flags anomalies automatically, and delivers a briefing to the exec team every morning before 8am. Mario pushed back on my original spec and built something more useful. That matters."

SN
Sandra Naguib
VP of Operations · MidEast Logistics Corp

"Most engineers optimize what you ask them to build. Mario interrogates whether you should build it at all, then architects around the constraint you actually have. The multi-agent pipeline he designed handles 40 concurrent document processing workflows. We could not have scaled our ops team fast enough otherwise."

MS
Mark Sobhy
Founder · Apex AI Ventures
Get Started

Free AI Automation Audit
Find Your Highest-ROI Opportunities

A 30-minute audit to map your current workflows, identify what can be automated, estimate the ROI, and tell you exactly what an AI system would need to look like to solve it. No commitment required.

You'll leave with a clear picture of where AI creates the most value in your operation — whether we work together or not.

What the audit covers
Current workflow bottleneck mapping
Automation feasibility & complexity score
Estimated hours saved per week
Recommended architecture approach
Realistic timeline & investment range
AI Readiness Assessment
Takes 3 minutes · Response within 24 hours

No commitment. No pitch deck. Just a conversation about what's worth building.