You will get Production AI MVP in 48 Hours — LangChain, Claude, FastAPI
Top Rated
Top Rated
Project details
Stop waiting months for an MVP. I am a Lead AI-Native Developer specializing in rapid, production-grade AI applications.
The market is flooded with beginners who simply copy-paste generated scripts that break in production. I bring actual computer science engineering rigor to AI-native development. My 2025 Cursor AI usage report verifies my extreme efficiency: I have processed over 3.15 Billion tokens and orchestrated 7,800+ autonomous agents.
By leveraging elite models like Claude alongside my native Ubuntu development environment, I architect systems at unmatched speeds without sacrificing scalability, maintainability, or security. Whether you need a sophisticated LangChain workflow, a custom database integration, or a full-stack MVP, I build robust systems designed to handle real users.
Please review my portfolio below to see my verified enterprise-level AI applications and RAG systems. Let’s turn your idea into a deployed, revenue-ready MVP in days.
The market is flooded with beginners who simply copy-paste generated scripts that break in production. I bring actual computer science engineering rigor to AI-native development. My 2025 Cursor AI usage report verifies my extreme efficiency: I have processed over 3.15 Billion tokens and orchestrated 7,800+ autonomous agents.
By leveraging elite models like Claude alongside my native Ubuntu development environment, I architect systems at unmatched speeds without sacrificing scalability, maintainability, or security. Whether you need a sophisticated LangChain workflow, a custom database integration, or a full-stack MVP, I build robust systems designed to handle real users.
Please review my portfolio below to see my verified enterprise-level AI applications and RAG systems. Let’s turn your idea into a deployed, revenue-ready MVP in days.
AI Algorithms
Generative Adversarial Network, Large Language Model, Multimodal Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI Mobile App Development, AI-Generated Code, AIOps, Conversational AI, Natural Language Generation, Natural Language UnderstandingAI Development Language
PythonAI Tools
Azure OpenAI, GitHub Copilot, Gradio, Hugging Face, PyTorch, Replit, Streamlit, TensorFlowAI Models
BERT, ChatGPT, GPT-4, LLaMA, OpenAI CodexWhat's included
| Service Tiers |
Starter
$79
|
Standard
$249
|
Advanced
$600
|
|---|---|---|---|
| Delivery Time | 2 days | 5 days | 10 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
2 reviews
(2)
(0)
(0)
(0)
(0)
This project doesn't have any reviews.
HS
Haris S.
Jul 28, 2026
AI Engineer / Forward-Deployed AI Engineer — LLMs, RAG, MCP, Agents & AI Systems
Outstanding work! Clean code, great communication, and delivered everything on time. Went above and beyond expectations. It was a pleasure working with M. Taha, and I'd gladly work with him again. Highly recommended!
lL
lior L.
Dec 19, 2025
Configure a Polymarket Trading Bot
About Muhammad
AI Agent Engineer | RAG, MCP, LLM Integrations & AI Automation
100%
Job Success
Tando Allahyar, Pakistan - 3:56 pm local time
I’m an AI Agent & Integration Engineer with 3+ years of experience building production AI systems. I help startups and teams turn AI ideas, prototypes, and existing systems into reliable products that can work with real users and real business data.
My focus is the engineering behind production AI, not just connecting an LLM API and calling it a product.
I build systems that can:
→ Use real business data and internal knowledge
→ Call APIs and external tools securely
→ Query databases with validation and permissions
→ Automate multi-step workflows
→ Retrieve and ground information reliably
→ Handle failures, retries, and edge cases
→ Be evaluated, tested, monitored, and deployed
𝗜 𝗰𝗮𝗻 𝗵𝗮𝗻𝗱𝗹𝗲 𝘁𝗵𝗲 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗶𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻 𝗲𝗻𝗱-𝘁𝗼-𝗲𝗻𝗱:
Requirements → Architecture → AI/LLM → Agents → RAG → Backend → APIs & Databases → Security → Evaluation → Testing → Deployment → Production
𝗪𝗵𝗮𝘁 𝗜 𝗕𝘂𝗶𝗹𝗱
★ 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 & 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻
Tool-calling agents, multi-agent systems, LangGraph workflows, routing, memory, retries, guardrails, evaluation, and human-in-the-loop workflows.
★ 𝗥𝗔𝗚 & 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗦𝘆𝘀𝘁𝗲𝗺𝘀
Document ingestion, hybrid/vector search, reranking, Graph-RAG, citations, access control, retrieval optimization, and hallucination guardrails.
★ 𝗠𝗖𝗣 & 𝗔𝗜 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀
Secure MCP servers connecting AI agents to PostgreSQL, APIs, internal tools, and business systems with controlled permissions and safe execution.
★ 𝗟𝗟𝗠 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀
OpenAI, Anthropic, Gemini, and AWS Bedrock integrations, structured outputs, caching, fallbacks, evaluation, and cost optimization.
★ 𝗧𝗲𝘅𝘁-𝘁𝗼-𝗦𝗤𝗟 & 𝗔𝗜 𝗗𝗮𝘁𝗮 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁𝘀
Natural-language analytics over PostgreSQL with schema-aware retrieval, SQL validation, read-only execution, query controls, auditing, and security.
★ 𝗗𝗼𝗰𝘂𝗺𝗲𝗻𝘁 𝗔𝗜 & 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻
OCR pipelines, document extraction, image processing, YOLO detection/tracking, and video analysis.
𝗦𝘆𝘀𝘁𝗲𝗺𝘀 𝗜'𝘃𝗲 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗕𝘂𝗶𝗹𝘁
★ 𝗦𝗲𝗰𝘂𝗿𝗲 𝗧𝗲𝘅𝘁-𝘁𝗼-𝗦𝗤𝗟 + 𝗠𝗖𝗣 𝗦𝗲𝗿𝘃𝗲𝗿
Built a production PostgreSQL system with AST-based SQL validation, read-only transactions, query cost controls, schema-aware RAG, REST API support, 158 tests, and 100% test coverage.
★ 𝗔𝗜 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝗔𝘀𝘀𝗶𝘀𝘁𝗮𝗻𝘁
Built a Text-to-SQL assistant over a 3M-row PostgreSQL database using AWS Bedrock, with validation, retries, caching, fiscal-calendar resolution, session memory, and auditing.
★ 𝗥𝗮𝗯𝘁 — 𝗚𝗿𝗮𝗽𝗵-𝗥𝗔𝗚 𝗳𝗼𝗿 𝗖𝗼𝗱𝗲𝗯𝗮𝘀𝗲𝘀
Built an AST and runtime-based Graph-RAG engine that reduced required LLM context by 𝟵𝟵.𝟮% compared with full-repository baselines.
★ 𝗟𝗮𝗿𝗴𝗲-𝗦𝗰𝗮𝗹𝗲 𝗢𝗖𝗥 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲
Built a 𝟮𝟬𝗠+ 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁 OCR preprocessing pipeline using Python/OpenCV with parallel processing and resume-safe execution.
★ 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 𝗣𝗶𝗽𝗲𝗹𝗶𝗻𝗲
Built a YOLOv8 + EfficientNet sports-analysis system achieving 𝟬.𝟵𝟱𝟰 𝗺𝗔𝗣𝟱𝟬 and 𝟵𝟲.𝟯% 𝘃𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆, while reducing manual review time by 𝟳𝟬–𝟵𝟬%.
𝗛𝗼𝘄 𝗜 𝗔𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝗔𝗜 𝗣𝗿𝗼𝗷𝗲𝗰𝘁𝘀
I care about what happens 𝗮𝗳𝘁𝗲𝗿 𝘁𝗵𝗲 𝗱𝗲𝗺𝗼.
Before choosing an agent, model, or framework, I look at the actual problem.
Sometimes an agent is the right solution.
Sometimes a deterministic workflow is safer.
Sometimes a smaller model is enough.
The goal isn't to use the most AI possible. The goal is to build the 𝗿𝗶𝗴𝗵𝘁 𝘀𝘆𝘀𝘁𝗲𝗺 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗽𝗿𝗼𝗯𝗹𝗲𝗺.
That means thinking about security, retrieval quality, evaluation, retries, observability, testing, performance, cost, and deployment, not just whether the LLM produces a good response.
You can bring me:
→ A one-paragraph AI idea
→ An existing codebase
→ A half-working prototype
→ A RAG system that isn't retrieving properly
→ An AI agent that needs better reliability
→ A database that needs a natural-language interface
→ An AI system that needs to move toward production
I'll help turn it into a system that actually works.
𝗞𝗲𝘆𝘄𝗼𝗿𝗱𝘀 𝗮𝘀𝘀𝗼𝗰𝗶𝗮𝘁𝗲𝗱 𝘄𝗶𝘁𝗵 𝗺𝘆 𝘀𝗸𝗶𝗹𝗹 𝘀𝗲𝘁:
AI Agent Developer, AI Engineer, AI Consultant, LLM Developer, Generative AI, Agentic AI, AI Automation, AI Integration, Multi-Agent Systems, AI Agents, Large Language Models (LLMs), GPT-4, OpenAI, Claude, Anthropic, Gemini, LLaMA, Mistral, AWS Bedrock, LangChain, LangGraph.
𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗦𝗼𝗺𝗲𝘁𝗵𝗶𝗻𝗴 𝗪𝗶𝘁𝗵 𝗔𝗜?
Tell me what you're building, what you already have, and where you're stuck.
I can help define the architecture, choose the right approach, build the system end-to-end, and take it from prototype to production.
Steps for completing your project
After purchasing the project, send requirements so Muhammad can start the project.
Delivery time starts when Muhammad receives requirements from you.
Muhammad works on your project following the steps below.
Revisions may occur after the delivery date.
Architecture & Scope Lock-in
We finalize the exact feature list, database requirements, and AI workflow. I set up the initial repository and development environment.
Rapid AI-Native Backend Development
Using Cursor and Claude, I rapidly build out the core logic, API endpoints (FastAPI), and integrate the necessary AI models or vector databases.