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I will be generative ai ml llm engineer ai agent ai chatbot python full stack developer
Ryan Daniels
About this gig
Your business has valuable data, but if customers still have to search through documents, repeat questions, or rely on manual processes, you need more than just AI. You need an intelligent system built around your data and business goals.
I build production-ready AI solutions including LLM-powered applications, AI chatbots, AI agents, and advanced Retrieval-Augmented Generation (RAG) systems. Using Python, OpenAI API, LangChain, LlamaIndex, and vector databases, I turn complex business data into intelligent, scalable solutions.
My Services:
- Advanced RAG System Development
- AI Chatbot Development
- AI Agent Development
- Full-Stack AI SaaS Development
- Vector Database & Semantic Search
- LLM Fine-Tuning & Prompt Engineering
- API Development & Cloud Deployment
Technologies: Python, OpenAI, LangChain, LlamaIndex, LLMs, RAG, Vector Databases, Semantic Search, AI Agents, GPT, Prompt Engineering, API Integration.
I focus on building reliable AI systems that understand your data, automate workflows, solve real business problems, and are ready for production.
Get to know Ryan Daniels
Ryan Daniels
I turn your product ideas into production ready designs
- FromUnited States
- Member sinceSep 2026
- Avg. response time1 hour
Languages
English, French, German, Italian
I’m a product design and mechanical CAD engineer specializing in SolidWorks, electronic enclosures, ESP32 & Arduino cases, PCB housings, sheet metal design, control panels, and DFM. I help turn concepts into production-ready 3D models optimized for 3D printing, CNC machining, and injection molding. From initial design and engineering to detailed CAD and manufacturing-ready files, I focus on precision, functionality, and clean professional results.
FAQ
Q: What do I need to get started?
A: You’ll need your OpenAI (or others) API key, and any documents or knowledge base if you want retrieval (PDFs, text, URLs, etc.). I’ll handle setup and integration.
Q: What technologies do you use for the full stack?
I specialize in the modern, scalable stack: Python with FastAPI for the backend, LangChain/LlamaIndex for LLM orchestration, and Next.js/React for the frontend (AI Website). Everything is containerized with Docker for easy deployment.
Q: What is the difference between a simple chatbot and an AI Agent?
A: A simple chatbot only answers based on pre-set knowledge. An AI Agent is much more powerful; it can reason, plan, and use tools (like fetching live data or performing calculations) to complete complex, multi-step tasks.
Q: Why do I need a RAG system if I'm using GPT-4?
A: Even the best LLMs have knowledge cut-offs and cannot access your private or proprietary data. A RAG system is essential because it grounds the LLM in your documents, guaranteeing accurate, company-specific answers and eliminating factual errors (hallucinations).
Q: What kind of data can your RAG system work with?
My RAG systems can index and retrieve information from almost any data source, including PDFs, CSVs, Excel, websites (sitemap/crawled data), Notion, databases
Q: Can the AI use my company data for answers?
A: Yes. That’s what RAG (Retrieval-Augmented Generation) does — it lets your AI reference your own documents securely.
