Muhammad Salman C.

I build AI into real products, and I make sure it holds up outside the demo. A lot of AI projects look impressive for five minutes, then fall apart in real use. They make things up, they answer from generic knowledge instead of the company's own data, and they never connect to the tools people already work in. That gap is what I close. I'm an AI developer focused on one thing: AI apps and integrations that work in production. I build with the OpenAI and Claude APIs, ground them in your own data, and wire them into the systems you already run. What I build: AI agents that carry out real tasks: reading, deciding, updating records and taking the next step on their own Chatbots and RAG assistants that answer from your documents, with sources, instead of guessing Voice agents that answer calls, understand the caller, and book or route from there AI features inside web apps, from the prompt layer to the interface your users actually touch LLM integrations that drop AI into your existing product or workflow through clean APIs Where I put the real effort is the part most people skip. Grounding answers in your data so the model does not invent things. Adding guardrails and human approval where a mistake would cost you. Watching token cost and response time so it stays fast and affordable. And testing against messy, real inputs, not just the happy path. I work hourly or fixed price, and you own the code and the prompts from day one. If you have an AI idea that needs to survive contact with real users, tell me what you are trying to do and I will give you an honest read on what it takes to get there.