Neo AI Engineer

What is Neo AI Engineer?

Neo is an autonomous AI agent designed to streamline and accelerate the work of AI engineers and ML researchers. It specializes in building, evaluating, and optimizing AI systems, including RAG pipelines, LLM evaluations, prompt optimization, fine-tuning, and ML training. Neo integrates seamlessly with popular development environments such as VS Code, Cursor, and Claude Code via MCP, allowing engineers to delegate complex ML tasks without leaving their IDE.

Key features include multi-step reasoning, a GPU sandbox for iterative experimentation, and an interactive chat interface. Neo can research approaches, write code, run experiments, debug failures, benchmark models, evaluate outputs, and produce detailed reports. It handles the entire engineering loop, from initial task prompt to final solution, automatically running hundreds of experiments to select the best model.

Benefits include a 10x faster ML development cycle, as demonstrated by Neo's #1 score on MLEBench in August 2025, where it outperformed competitors like RD-Agent and AIDE in 75 competitions. Neo is used by ML engineers and researchers worldwide and runs on your own GPU cloud or with zero setup in the cloud.

Use cases span the full spectrum of AI engineering: building RAG systems, running LLM evals, optimizing prompts, preparing datasets, fixing training pipelines, analyzing data leakage, adding new AI features to brownfield projects, and generating reports. Neo is particularly valuable for teams looking to ship production AI faster by automating repetitive engineering tasks and reducing manual debugging.

Technical details: Neo uses multi-step reasoning with an extensive knowledge base and GPU sandbox to perform iterative ML experimentation. It proactively explores multiple approaches, assesses outcomes, and evaluates risks to find the most effective solution. The agent can be controlled via an interactive chat interface, allowing engineers to guide its exploration and provide context. Neo works with Claude Code, Cursor, VS Code, and Open VSX, and can be installed as an extension or run in the cloud.

Key Features

autonomous AI agent multi step reasoning GPU sandbox interactive chat interface RAG pipeline building LLM evaluation prompt optimization fine tuning ML training automated experimentation

Who is it for?

AI engineers, ML researchers, ML engineers, AI researchers, data scientists, AI startups