Visible project loop
Connect project context, plan the run, execute with tools, and review changes before they land.
No hosted data backend. Your projects, prompts, files, chats, and agent memory stay on your devices. You own backup and recovery.
NexaAct is designed for users who want AI agents to work inside a local desktop workspace instead of staying inside a single hosted chat box. It has no hosted backend for workspace data, so projects, conversations, prompts, files, and agent memory remain on systems you control. You own backup and recovery responsibility.
The core difference is control: users bring the accounts, APIs, repositories, Cloudflare infrastructure, and habit-skill memory they want the agent to use.
Learn how NexaAct works as a desktop AI agent
Connect project context, plan the run, execute with tools, and review changes before they land.
Use OpenAI, Claude, Gemini, DeepSeek, Qwen, OpenRouter, or your own compatible API endpoint.
Plan, execute, and review project work from one desktop session.
Add OpenAI-compatible endpoints, internal gateways, or hosted providers.
Manage signed-in model accounts and API-backed models for separate projects or billing boundaries.
Control a running desktop workspace through your own Cloudflare deployment.
NexaAct connects to files, repositories, browser workflows, account routing, and local execution instead of only exchanging messages.
Signed-in accounts and self-supplied APIs can live together, so the user can change models without rebuilding the workspace.
Durable signals become inspectable skill files, section indexes, and narrow instructions that can evolve with the user.
habit-skill turns long-term preferences, solved lessons, tool choices, and collaboration patterns into a clean skill folder that the AI can maintain over time. It is not a raw chat memory dump: NexaAct routes through a root skill, section indexes, and focused skill files so the agent can reuse the right behavior without carrying unrelated history.
The AI decides whether a detail has future value before writing it into the habit-skill system.
Root rules choose the right major section, then section indexes point to the narrowest matching skill file.
Complete habit-skill folders can be imported, exported, inspected, and kept maintainable as the user evolves.
NexaAct is not tied to a single model vendor. The model menu, provider accounts, context windows, and custom endpoints are managed directly in the desktop app.
Add, switch, and manage the third-party accounts your agent can use for deployments and pushes.
Extend the agent with reusable instruction packs, connected tools, browser control, service integrations, and repeatable workflows from a browsable product surface.
Your computer remains the NexaAct runtime, while your phone or another device becomes a remote control surface. Prompts, files, chats, and workspace data stay under your control: NexaAct has no hosted backend for this data, does not collect local data, and uses the Cloudflare infrastructure you deploy and manage yourself.
View remote control details
NexaAct is a free desktop AI workspace for project-aware coding sessions, model provider accounts, custom APIs, GitHub and Cloudflare deployment accounts, remote control, and self-evolving habit-skill memory.
Yes. NexaAct keeps signed-in provider accounts and self-supplied API models available in the same workspace, so a conversation can switch models without manually changing accounts or keys.
Habit-skill is NexaAct’s maintainable memory model. It stores durable preferences, solved lessons, software choices, and collaboration patterns as focused skill files instead of dumping raw chats into memory.
No. NexaAct remote control is designed around infrastructure the user deploys and controls in their own Cloudflare account.