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I will build custom ai web application or rag chatbot using gemini API
Ahmad Chughtai
About this gig
Are you looking to integrate high-performance Artificial Intelligence into your platform or build a custom RAG (Retrieval-Augmented Generation) application from scratch?
I am Ahmad, an AI Application Engineer and Full-Stack Developer specializing in building robust, production-ready AI systems. I don't just write basic API calls, I engineer complete, secure, and scalable AI solutions tailored to your specific workflows.
Whether you need a contextual AI chatbot that reads your private documents, an interactive smart dashboard, or an automated text summarization pipeline, I deliver fully functional, deployable systems ready for immediate use.
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Get to know Ahmad Chughtai
Ahmad Chughtai
AI Application Engineer and Full Stack Web Developer
- FromPakistan
- Member sinceSep 2021
Languages
Urdu, English
I’m Ahmad, an AI Application Engineer and Full-Stack Developer. I don't just write features—I build complete, high-performance systems from database architecture to scalable AI. Whether you need a custom web app, automated workflow, or interactive dashboard, I deliver production-ready solutions that solve real-world problems. Let’s build something great—message me today!
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FAQ
What do I need to get started with the project?
You will need a clear idea of what you want the AI to achieve, your primary business data (if building a RAG chatbot), and access to a Gemini API key. If you don't have an API key yet, I can guide you through generating one in Google AI Studio.
Will the RAG chatbot hallucinate or make up false information?
Standard LLM calls can hallucinate, but a properly configured RAG (Retrieval-Augmented Generation) pipeline forces the AI to answer strictly using your provided documents/knowledge base. I implement strict prompt guardrails and chunking strategies to minimize false answers.
What data formats can the RAG system ingest?
The system can ingest and index PDFs, text files, CSVs, JSON data, markdown, and live relational databases.
Who pays for the API usage costs?
You will be responsible for your own Gemini API usage. Google offers generous free-tier access for Gemini models, which is often sufficient for development and early usage.
Can you deploy the application to my server or cloud provider?
Yes! I can package the application using Docker and deploy it to VPS platforms like Hetzner, AWS, Vercel, Render, or DigitalOcean upon request.
