You will get custom machine learning and ai solutions using python
Project details
I am a Machine Learning Engineer specializing in AI, NLP, and deep learning, offering custom, portfolio-backed ML solutions for real-world problems.
I work on end-to-end machine learning pipelinesfrom understanding your data and objectives to building, evaluating, and delivering reliable ML models.
What I can help you with:
Machine learning models (classification, regression, recommendation systems)
NLP solutions (sentiment analysis, text classification, chatbots)
Deep learning models using PyTorch
AI-based recommendation systems
Data preprocessing, feature engineering & model evaluation
Why choose me:
Real project experience (portfolio-backed)
Clean, well-documented Python code
Clear communication & on-time delivery
Custom solutions (not copy-paste)
I work on end-to-end machine learning pipelinesfrom understanding your data and objectives to building, evaluating, and delivering reliable ML models.
What I can help you with:
Machine learning models (classification, regression, recommendation systems)
NLP solutions (sentiment analysis, text classification, chatbots)
Deep learning models using PyTorch
AI-based recommendation systems
Data preprocessing, feature engineering & model evaluation
Why choose me:
Real project experience (portfolio-backed)
Clean, well-documented Python code
Clear communication & on-time delivery
Custom solutions (not copy-paste)
Machine Learning Tools
Azure Machine Learning, BERT, ChatGPT, deeplearn.js, Deeplearning4j, GitHub Copilot, Google Sheets, GPT-3, Keras, Microsoft Excel, MLflow, NLTK, NumPy, pandas, Python, Python Scikit-Learn, PyTorch, scikit-learn, SciPy, SQL, TensorFlow, TextBlob, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$50
|
Standard
$70
|
Advanced
$100
|
|---|---|---|---|
| Delivery Time | 2 days | 3 days | 4 days |
Number of Revisions | 2 | 4 | 5 |
Number of Model Variations | 3 | 5 | 5 |
Number of Scenarios | 2 | 3 | 5 |
Number of Graphs/Charts | 2 | 4 | 6 |
Model Validation/Testing | |||
Model Documentation | - | - | |
Data Source Connectivity | - | - | |
Source Code | - |
About Saad
AI Engineer & Web Developer | Next.js | AI Agents | RAG | SaaS Apps
Islamabad, Pakistan - 9:20 am local time
Most AI demos look impressive… until they break in production. That’s where I come in.
👋 I'm an Agentic AI Engineer and Full-Stack Developer with 4+ year of production experience building LLM-powered systems, autonomous agents, and full SaaS products for real clients. I've delivered an 85% ticket deflection rate with a LangGraph support agent, automated 70% of inbound calls with a voice AI on Whisper + GPT-4o, and built multi-tenant SaaS platforms that drove 40% enterprise upsell increases. I don't prototype and hand off. I build the thing, deploy it, and make sure it runs.
🚀 WHAT I BUILD (END-TO-END)
✔ Full-stack SaaS applications with AI embedded as core product features
✔ Agentic systems and knowledge bots that run autonomously in production
✔ Service and marketing sites with performance metrics that actually matter
✔ Multi-tenant platforms with Stripe billing, RBAC, and workspace isolation
✔ Internal dashboards, admin panels, and role-based tools
✔ Workflow automation connecting AI to real business systems and APIs
🧱 FULL-STACK WEB DEVELOPMENT
This is the core. I build complete, production-grade web products from scratch — not just the AI layer.
FRONTEND:
✔ Next.js 14 (App Router, Server Actions, SSR, ISR, streaming UI)
✔ React 18 (hooks, context, optimistic updates)
✔ Tailwind CSS, Shadcn UI, Radix UI, Framer Motion
✔ Performance: Lighthouse 95+ on mobile, LCP under 2.5s on 4G, Framer Motion animations at 60fps / sub-16ms interaction latency, Cloudinary CDN with q_auto/f_auto delivering 60% image payload reductions, Core Web Vitals tuned
BACKEND:
✔ Node.js with Express (REST APIs, middleware, auth layers)
✔ FastAPI (AI microservices, async endpoints, background tasks)
✔ tRPC (type-safe API layer for Next.js full-stack apps)
✔ Redis (caching, session management, queue-backed jobs)
Database and Auth:
✔ PostgreSQL — schema design, materialized views, composite indexing, server-side pagination over millions of rows, sub-200ms query times under production load
✔ Supabase (auth, realtime DB, storage, vector, row-level security, workspace isolation)
✔ Prisma ORM, MongoDB
SaaS Features I Build:
✔ Multi-tenant architecture with workspace isolation and zero data bleed
✔ Stripe billing: subscriptions, usage-based metering, webhook-driven plan upgrades
✔ RBAC, scoped permissions, invite flows, and audit logs
✔ White-label dashboards with cohort analytics, CSV exports, and live metric ingestion
✔ AI features embedded into the product: chat widgets, quote bots, support agents, content pipelines
DEPLOYMENT:
✔ Docker (containerised services, multi-stage builds)
✔ Vercel (Next.js, edge functions, preview deployments per branch, zero-downtime rollouts)
✔ AWS, Render (backend API hosting and scaling)
✔ GitHub Actions (CI/CD pipelines, automated deploys)
🤖 AGENTIC AI SYSTEMS (PRODUCTION-LEVEL)
Most web developers add an API call to GPT and call it AI. I build the actual systems: agents with memory, tool use, multi-step reasoning, stateful orchestration, and fallback handling that run without supervision.
✔ Multi-agent systems with inter-agent communication (LangGraph state machines, CrewAI role-based pipelines, AutoGen collaboration flows)
✔ Tool-calling agents with function calling, JSON schema tools, and chained API actions
✔ Stateful agents with persistent memory (vector stores, session history, conversations)
✔ Async and background execution (Python async, FastAPI workers, Celery/queue-based systems)
Tech Stack:
LangGraph (state machines, multi-agent orchestration)
LangChain (chains, tools, memory, document loaders, AgentExecutor)
CrewAI (role-based agent collaboration)
OpenAI Agents SDK (tool use, handoffs, streaming)
GPT-4o, GPT-4o mini, Assistants API, function calling
Anrhropic Claude (tool use, long-context reasoning)
🧠 RAG AND KNOWLEDGE SYSTEMS
✔ Production RAG pipelines for enterprise knowledge bases — not demo notebooks
✔ Document ingestion (PDF, CSV, DOCX, web scraping), chunking strategies, embedding + similarity search
✔ Re-ranking and hybrid retrieval (BM25 + vector, MMR, top-k), sub-second retrieval in production
Vector DBs: Pinecone, FAISS, ChromaDB, Supabase Vector
🏗️ WHAT I'VE ACTUALLY SHIPPED
✔ SaaS Dashboard — multi-tenant, Stripe metering, sub-200ms queries, GPT-4o bot, 40% upsell increase
✔ FiTusion — 12k+ users, Lighthouse 95+, LCP 2.5s, AI assistant, 60% image reduction
✔ InstantRepair — mobile-first, 60fps animations, GPT-4o quote bot, lead conversion lift
✔ Real Estate — SSG + ISR, JSON-LD rich results, AI property recommendation chatbot
✔ Bistro OS — Flutter app on Android, Firebase sub-second sync, role-based UI, AI upsell
✔ Voice AI — Whisper + GPT-4o + Twilio, 70% calls automated, 60% handle time cut
✔ Lead Gen Agent — Playwright + GPT-4o ICP scoring, 500+ leads/day
Have a project? SEND A MESSAGE and tell me what you're building.
Steps for completing your project
After purchasing the project, send requirements so Saad can start the project.
Delivery time starts when Saad receives requirements from you.
Saad works on your project following the steps below.
Revisions may occur after the delivery date.
Requirement Analysis
I will review your project details, dataset, and objectives to understand the problem and define the best solution approach.
Data Preprocessing & Exploration
Clean, analyze, and prepare the dataset. Handle missing values, feature engineering, and exploratory analysis.