Daytona vs Neo: Side-by-Side Comparison (2026)

Daytona: Isolated sandbox infrastructure for securely executing AI-generated code. built by Daytona. Core capabilities include Sub-90ms isolated sandbox creation for AI-generated code execution, Stateful, long-running sandbox environments for persistent AI agents, Environment snapshots with save, restore, and resume capabilities..

Neo: Agentic AI control platform for SecOps to govern autonomous AI tools at runtime. built by Neo. Core capabilities include Lightweight endpoint agent for AI tool discovery and inventory, Real-time policy enforcement at application runtime, LLM-assisted policy authoring and deployment..

Both serve the Agentic AI Security market but differ in approach, feature depth, and target audience.

Daytona differentiates with Sub-90ms isolated sandbox creation for AI-generated code execution, Stateful, long-running sandbox environments for persistent AI agents, Environment snapshots with save, restore, and resume capabilities. Neo differentiates with Lightweight endpoint agent for AI tool discovery and inventory, Real-time policy enforcement at application runtime, LLM-assisted policy authoring and deployment.

Daytona is developed by Daytona. Neo is developed by Neo. The vendor behind a product decides its roadmap, support, and longevity, so check each company's profile before you commit.

Daytona integrates with VS Code, Git. Neo integrates with Claude Code, Gemini CLI, GitHub Copilot, OpenAI Codex, ChatGPT desktop and 5 more. Check integration compatibility with your existing security stack before deciding.

Daytona and Neo serve similar Agentic AI Security use cases: both are Agentic AI Security tools, both cover Agentic AI Security, LLM Security, AI Governance. Review the feature comparison above to determine which fits your requirements.