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Meet Neo

Neo is a local-first AI engineering agent that plans, executes, and iterates on complex AI, ML, and data workflows directly inside your VS Code environment.

Neo works across traditional machine learning, generative AI, and agentic systems by analyzing your codebase, data, models, and execution history to take concrete, inspectable actions.

Install VS Code ExtensionExplore AI and ML Use Cases

What Neo Does

Neo functions as an AI engineering agent that can understand goals, plan multi-step execution, run code locally, and adapt based on results while keeping you fully in control.

Agentic AI workflows

Neo breaks down high-level objectives into executable steps across data preparation, ML training, LLM workflows, evaluation, and iteration. It analyzes tasks before acting and adjusts strategies based on outcomes.

Inspectable and reproducible outputs

Every action produces concrete artifacts including code, prompts, configurations, metrics, reports, and models that live in your repository and can be edited, versioned, or rerun.

Context aware reasoning

Neo reads your project structure, schemas, experiment history, prompts, model checkpoints, and prior runs to make informed decisions rather than starting from scratch each time.


How Engineers Use Neo

Neo supports real AI engineering work beyond single-shot code generation.


Platform vs VS Code Extension

Neo works in both the web platform and VS Code. Engineers typically use the VS Code extension for deeper control over execution, data, and version control.

Platform Mode VS Code Extension
SetupInstant, no local setup requiredInstall once inside VS Code
ExecutionManaged cloud environmentLocal-first execution with optional cloud access
Data AccessFile uploads (50MB limit) or cloud storageLocal files (no size limits) plus cloud integrations
Code ControlDownload generated artifactsEdit, run, debug, and commit directly in IDE
Best ForQuick experiments and sharing resultsProduction-grade AI and ML development

End-to-End AI and ML Lifecycle Support

Neo assists across the full lifecycle of modern AI systems while keeping all decisions transparent and reversible.

Data and Knowledge Sources → Feature or Context Engineering → Model or LLM Execution → Evaluation → Iteration and Refinement

This applies to traditional ML pipelines, generative AI systems, and agent-based workflows.


Get Started in VS Code

Install the VS Code Extension and run your first AI task →


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