I will build production ai agents, rag chatbots and llm applications


Über diesen Service
I build production-ready AI applications using Large Language Models (LLMs), AI agents, multi-agent workflows, Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP).
With over 8 years of experience in Machine Learning and Computer Vision, I develop scalable AI solutions that integrate LLMs with business data, APIs, databases, and external tools.
My services include AI agents, multi-agent systems, AI chatbots, RAG applications, MCP servers and clients, workflow automation, tool calling, function calling, vector database integration, FastAPI development, Docker deployment, and cloud-ready architectures.
I work with OpenAI, Claude, Gemini, Llama, Qwen, LangGraph, LlamaIndex, Qdrant, Pinecone, PostgreSQL, FastAPI, Docker, Kubernetes, AWS, and Azure.
Every solution is designed for production with clean architecture, maintainable code, scalability, security, and performance in mind.
Please contact me before placing an order so we can discuss your requirements and choose the right solution for your project.
Lerne allenmistry kennen
Sunil Panchal
- AusIndien
- Mitglied seitSept. 2018
- Letzte Lieferung4 Jahre
Sprachen
Englisch, Hindi
FAQ
What AI solutions do you build?
I build AI agents, multi-agent workflows, AI chatbots, RAG applications, MCP servers and clients, workflow automation, knowledge assistants, and custom LLM-powered applications for web and enterprise use cases.
Which AI models and frameworks do you work with?
I work with OpenAI, Claude, Gemini, Llama, Qwen, LangGraph, LangChain, LlamaIndex, FastAPI, Qdrant, Pinecone, PostgreSQL, Docker, Kubernetes, AWS, and Azure. I can also integrate other APIs or open-source models based on your requirements.
Can you integrate my existing systems and APIs?
Yes. I can integrate your AI application with REST APIs, databases, CRMs, ERP systems, Slack, Microsoft Teams, Google Workspace, and other third-party services.
Can you deploy the application?
Yes. I can containerize your application using Docker and help deploy it on AWS, Azure, GCP, or your own Linux server. Deployment requirements can be discussed before starting the project.
What do you need before starting the project?
A brief description of your use case, preferred AI model (if any), existing documentation or APIs, data source or knowledge base, deployment preference, and expected outcome are enough to get started.
Do you build production-ready applications?
Yes. I focus on production-ready architecture with clean code, modular design, scalability, security, logging, and maintainability. The solution is designed to support future enhancements as your business grows.
