Best Private AI Agents: How to Pick One That Keeps Your Data Yours

What does “private” mean for an AI agent?

It comes down to where it runs, where the AI model runs, what it keeps and what it can reach. Get those four answers and you know who can see your data.

• Where the agent runs: your device, a server you rent, or the maker’s cloud.
• Where the model runs: the agent and the model doing the thinking are often in different places.
• What it keeps: memory, screenshots, transcripts, and whether any of it trains someone’s model.
• What it can reach: files, accounts, passwords and cards, and what it does without asking.

Where does it run?

On your device is the most private, a server you control comes next, and the maker’s cloud means trusting the maker. Each step outward adds someone who could, in principle, see your data.

• On your device. The agent lives on your computer or phone. Your files and history stay on your disk.
• On your own server. You run it on a rented server or a spare machine at home, so it can work while your laptop is closed. You control the setup; on a rented server, the hosting company runs the hardware.
• In the maker’s cloud. Easiest to start, nothing to install. Your data sits on their systems, under their privacy policy.

Where does the model run?

Check this separately, because a local app can still send your words to a cloud model. This is the most common gap between “runs on your computer” and “private”.

Atticus is a good example of an honest split. The app lives on your Mac and turns your speech into text there, so audio never leaves the Mac. The thinking runs on your Claude plan. AirJelly keeps its screenshots encrypted on your device, and says plainly that relevant content goes to the cloud when you use its AI features.

Neither is hiding anything. They just aren’t fully local. If you want nothing to leave your machine, you need an agent that can use a local model: one that runs on your own hardware through a tool like Ollama or LM Studio.¹Note 1 Ollama and LM Studio are free apps that download open models and run them on your own computer. An agent that supports them can send its requests there instead of to a cloud provider.

Does your data train someone’s model?

Look for a plain “no” on the maker’s privacy page, and check the model provider’s terms too. AirJelly, for example, states that your content doesn’t train its models.

With open-source agents, the agent’s maker usually never sees your data at all. What matters then is the AI provider you connect. Read its data terms, or skip the question entirely with a local model.

How long does it keep things?

Memory is what makes an agent useful, so you want memory you can see, edit and delete. An agent that remembers your preferences is better. One that quietly keeps everything forever is a risk.

Good signs: memory stored in files on your own disk, a way to pause capture or exclude apps, and a clear delete. Xiryn keeps conversations, memory and keys in one file on your disk. AirJelly lets you pause capture or exclude specific apps.

What can it reach?

Give an agent the least access that gets the job done, and prefer agents that fence themselves in. The privacy risk isn’t only who sees your data. It’s what the agent can do with it.

• Its own sandbox. NanoClaw runs every session in its own container, so the agent only sees the files and credentials you hand it. Xiryn gives each agent its own desktop on your computer, away from your screen and files.
• Keys it never holds. NanoClaw routes requests through a credential vault by default, so agents never hold raw API keys.
• Approval before it acts. Atticus asks before it buys, sends or deletes anything. Xiryn pays for nothing until you approve.

Bring your own key, or your own model

Bring-your-own-key means you pick the AI provider and own the account; a local model means there’s no provider at all. Most open-source agents support both.

With your own key, your prompts go straight from your machine to the provider you chose, under your account and its terms. With a local model, they never leave. The trade-off is power: local models are smaller than the biggest cloud models, and they need a capable computer to run well. Some agents let you mix the two: NanoClaw, for one, lets each group of agents use a different provider, so sensitive work can stay on a local model.

A quick privacy checklist

Five questions to ask before you give any agent your inbox.

1. Where does the agent run? Your device, your server, or theirs?
2. Where does the model run, and can you choose it? Look for bring-your-own-key and local model support.
3. Does your data train anything? You want a clear no, from the maker and the model provider.
4. Can you see and delete what it remembers? Files on your disk beat a black box.
5. What can it touch without asking? Sandboxed sessions and approval before spending or sending are the good signs.

Some listings on AIcensus include a privacy section with the points the maker states, linked to the maker’s own privacy page.

The best private AI agents

These agents pass the checklist on their own terms; open each card for what it runs on and what it costs. Each claim below comes from the maker’s own site.

Fully on your device

Underdog is a personal assistant for email, calendar, meeting notes, dictation and errands, and says its AI runs entirely on your device. Your mail syncs directly with your email provider. It’s the closest thing here to a private assistant that needs no setup.

Open-source assistants you run yourself

• OpenClaw is the best-known open-source personal assistant. It runs on your own machine, you reach it through messaging apps, and it can use local models through Ollama, LM Studio or llama.cpp. There’s no hosted version.
• Hermes Agent from Nous Research is open source and remembers you over time. It runs on your laptop, a small rented server or a server that sleeps when idle, and can run open models entirely on your own machine, including through Ollama. Hermes Agent vs OpenClaw puts the two side by side.
• NanoClaw is the small, readable alternative to OpenClaw, with each session in its own container. Claude is the default provider, and any group of agents can switch to a local model through Ollama.
• Xiryn has no accounts and no servers, and its own home page says that with a local model not even your prompts leave your computer.

Looking further? See the OpenClaw alternatives and Hermes Agent alternatives.

A general agent on your own computer

Goose is an open-source agent with a desktop app and command line for research, writing, automation, analysis and code. It works with many model providers, including local runners like Ollama, LM Studio and Docker Model Runner, and it’s looked after by an open foundation rather than a single company.

Local apps that use a cloud model

Atticus and AirJelly keep your data on your Mac or PC but send the AI part to the cloud. They’re a good fit if you want local storage and clear controls, and you’re comfortable with a cloud model doing the thinking.

Coding agents that work with local models

If the private data is your code, Aider, Cline and OpenCode are open source and can run on local models. Compare them with the cloud-first options in Aider vs Claude Code and Codex vs OpenCode, or read how to choose an AI coding agent.

What about a private AI server?

A private AI server is the same open-source agent on a machine you control, so it can work while your laptop is closed. Hermes Agent and OpenClaw both document running on a server, and OpenClaw’s docs cover Docker and even a Raspberry Pi.

A rented server is private from the agent’s maker, not from the hosting company. For the strictest setup, run the agent at home or pair the server with a local model, which needs a machine with a good graphics card.

A quick way to decide

If you want private with no setup, start with an on-device assistant; if you want full control, run an open-source agent with a local model. Then use the checklist above on anything else you’re considering.

Not sure which kind of assistant you need? How to choose an AI personal assistant walks through the rest of the decision.