Frequently Asked Questions

RAG (Retrieval Augmented Generation) is an architecture that grounds LLM responses in specific data sources rather than relying solely on training data. It works by retrieving relevant documents from a vector database (like Qdrant or PostgreSQL/pgvector), then providing that context to the LLM for accurate, hallucination-resistant responses. RAG is crucial for business applications requiring factual accuracy, data privacy, and domain-specific knowledge.

I offer four main service categories: (1) AI Agent Development - building autonomous multi-agent systems for business automation, (2) RAG Pipeline Architecture - designing production-grade retrieval systems with vector databases, (3) Security Engineering - web app pentesting, AI red teaming, and secure architecture review, and (4) Full-Stack Development - end-to-end web applications using Next.js and FastAPI. I also provide consulting and advisory services.

AI red teaming is the practice of systematically testing AI systems for security vulnerabilities, particularly prompt injection attacks, jailbreak attempts, and output manipulation. As businesses deploy AI systems that interact with sensitive data or make decisions, red teaming identifies weaknesses before malicious actors do. I conduct comprehensive AI security assessments using both automated tools and manual testing methodologies.

My core stack includes: Frontend (Next.js 15, React 19, TypeScript, Tailwind CSS), Backend (FastAPI, Python, Node.js), AI/ML (OpenAI Agents SDK, Gemini SDK, Claude API, LangChain), Databases (PostgreSQL with pgvector, Qdrant vector database), DevOps (Vercel, Docker, cloud deployment), and Automation (n8n workflows). This full-stack capability allows me to architect complete systems from database to UI.

Timeline depends on complexity: A basic single-agent system with 2-3 tools takes 1-2 weeks ($2,500-$5,000). A multi-agent orchestration with RAG integration and human-in-the-loop controls takes 2-4 weeks ($5,000-$15,000). Enterprise systems with complex integrations, SSO, and SLA requirements take 4-8 weeks ($15,000+). I provide detailed timelines during project scoping.

Three key differentiators: (1) Security-first architecture - I apply security engineering principles to AI systems from day one, (2) Context grounding expertise - I specialize in techniques that minimize AI hallucination through proper RAG implementation and validation, and (3) Full-stack delivery - I can build complete systems including vector databases, APIs, and user interfaces, not just AI components. This ensures cohesive, production-ready solutions.

Yes, I work with clients globally. I'm based in Pakistan (PKT, UTC+5) but have successfully delivered projects for US, European, and Middle Eastern clients. I communicate primarily via email and video calls, with flexible scheduling to accommodate different timezones. Payment is accepted via bank transfer (Wise, Payoneer), cryptocurrency (USDC, ETH), or PayPal for smaller projects.

The process is: (1) Initial consultation - discuss requirements, timeline, and budget, (2) Proposal - detailed scope, deliverables, and pricing, (3) Kickoff - 50% upfront payment and project initiation, (4) Development - regular async updates and milestone reviews, (5) Delivery - remaining payment, code handover, deployment, and knowledge transfer, (6) Support - 30-day post-launch bug fix support included.

Absolutely. My portfolio at sheikhmujtaba.me showcases 25+ projects including: (1) CRM Digital FTE - an autonomous customer success platform with AI agents, (2) AI Employee Digital FTE - a 9-service orchestrated business automation system, (3) NuraShell - a CLI AI agent published on PyPI, and (4) Various full-stack applications with AI integration. Each project includes code repositories, live demos, and detailed descriptions.