Nouman B.

Most AI products look impressive in a demo. The real challenge is making them reliable, accurate, scalable, and useful in production. I build AI-powered applications using Python, LLMs, RAG, AI agents, and modern AI APIs, taking ideas from prototype to production. I work on AI systems that connect models with real business data, knowledge bases, APIs, databases, and cloud infrastructure. Whether you’re building an AI SaaS product, intelligent chatbot, RAG system, agentic workflow, or AI automation platform, I can help turn the idea into a working product. What I Build • LLM Applications: OpenAI, Claude, Gemini and custom LLM integrations • RAG Systems: Document processing, embeddings, vector search and knowledge bases • AI Agents: Tool-using agents, multi-step workflows and autonomous task execution • AI Chatbots: Customer support, internal assistants and conversational AI • AI Automation: Repetitive business processes powered by LLMs and agents • AI APIs & Backend Systems: Python, FastAPI, .NET/C#, Node.js and production AI services • AI Data Pipelines: ETL, document processing, large datasets and background workflows • Cloud & Deployment: AWS, Azure, Docker and scalable AI deployments • AI Integrations: Connecting AI models with databases, SaaS platforms and third-party APIs • Performance & Scalability: Optimizing AI applications, APIs, databases, latency and high-volume workloads I focus on the part that matters after the demo: accuracy, reliability, latency, cost, scalability, monitoring, and real-world edge cases. I’ve worked on systems processing 1M+ transactions/month and financial workflows handling roughly $500K/month, bringing the same production mindset to AI applications. If you’re building an AI product and need someone who can take it from idea → AI prototype → production, tell me what you’re building and what you want the AI to accomplish.