I will engineer an autonomous llm agent with web automation


About this gig
Don't settle for a basic chatbot that just regurgitates text. I build autonomous GenAI agents that take action, pull live data, and integrate seamlessly into your business workflows.
As an AI Engineer specializing in generative AI and tool-calling architectures, I go beyond simple "ChatGPT wrappers." I architect intelligent agents that can reason through complex tasks, scrape and analyze external data, and execute custom actions (like API calls to Google Maps, databases, or your internal software).
What I can build for you:
Autonomous Data Agents (Automated data extraction, scoring, and structuring)
RAG Pipelines (Chat with your own private PDFs, databases, or knowledge bases)
Custom GPTs with Advanced Actions (API integrations and code execution)
Interactive AI Dashboards (Gradio, Streamlit) or Backend API Endpoints
Whether you need a backend script that automates hours of manual data entry or a fully deployed RAG application, I deliver clean, documented, and production-ready Python code.
*** PLEASE MESSAGE ME WITH YOUR PROJECT SCOPE AND DATA SOURCES BEFORE PLACING AN ORDER ***
Get to know Metin A
AI Engineer
- FromTurkey
- Member sinceAug 2022
- Avg. response time1 hour
Languages
English, Turkish, Japanese
My Portfolio
Other AI Development Services I Offer
FAQ
What is the difference between a normal chatbot and an autonomous agent?
A standard chatbot simply answers questions based on its pre-trained memory. An autonomous agent is equipped with "tools" (Custom Actions). This allows the AI to interact with the outside world to complete multi-step reasoning tasks.
Which LLM providers do you work with?
I specialize in architectures utilizing Google Generative AI (Gemini), specifically leveraging their advanced function-calling and code-interpreter capabilities. If you require open-source models (like Llama) deployed locally for strict data privacy, please message me to discuss hardware constraints
Can you integrate the AI agent with my own private data?
Absolutely. I build RAG (Retrieval-Augmented Generation) pipelines using vector databases. This allows the AI agent to securely search, read, and cite your private documents, PDFs, or internal wikis to provide accurate answers without "hallucinating" or making up facts.

