NEO is an autonomous ML engineer that uses a multi-agent system powered by state-of-the-art LLMs and a reasoning engine to automate end-to-end data science and ML workflows—handling EDA, data cleaning, feature engineering, model training and fine-tuning, evaluation, RAG pipelines, Evals, and deployment. It runs iterative experiments in a GPU sandbox, coordinates specialized agents to reduce errors and hallucinations, supports integrations like VS Code, Snowflake, BigQuery and Databricks, and offers a chat-driven human-in-the-loop interface plus easy knowledge-base customization. Use NEO to eliminate repetitive grunt work, speed up model optimization and iteration, and deliver production-ready AI systems faster.