Aug 13 - How to Build Vision Data Agents with Tools, Skills, and MCP

In this session, you’ll learn how to build production-ready AI agents that can reason over your data, automate complex tasks, and integrate seamlessly into your existing stack using tools, skills, and the Model Context Protocol (MCP).

Date, Time and Location

We’ll walk through how modern agentic systems move beyond simple prompts—leveraging structured tools like dataset operations, embeddings, evaluation pipelines, and model execution to take real action. You’ll see how these agents can tag data, run inference, evaluate performance, and surface insights automatically, all within a unified workflow.

By combining natural language interfaces with programmable building blocks, teams can dramatically reduce manual effort, accelerate experimentation, and unlock faster decision-making across the ML lifecycle.

Whether you're building data-centric AI systems, managing large-scale vision datasets, or exploring agentic workflows for the first time, this session will give you a practical blueprint for getting started.

*About the Speaker*

Adonai Vera \- Machine Learning Engineer & DevRel at Voxel51\. With over 7 years of experience building computer vision and machine learning models using TensorFlow\, Docker\, and OpenCV\. I started as a software developer\, moved into AI\, led teams\, and served as CTO\. Today\, I connect code and community to build open\, production\-ready AI\, making technology simple\, accessible\, and reliable\.