# Private alternatives to ChatGPT for work in 2026

> Six private ChatGPT alternatives compared by retention, training, local storage, model quality, and fit for confidential professional work.

- Canonical URL: https://www.opensoftware.co/blog/private-alternatives-to-chatgpt-for-work
- Published: Jul 20, 2026
- Updated: Jul 20, 2026
- Category: Guides
- Author: OpenSoftware
- Reading time: 12 min read
- Topics: private ChatGPT alternative, private AI for work, ChatGPT alternative for business, confidential AI assistant, local AI assistant, zero retention AI

## Primary links

- [Learn more about June](https://www.opensoftware.co/june)
- [Download June](https://www.opensoftware.co/download/mac)
- [June community](https://t.me/osjune)
- [Open source repository](https://github.com/open-software-network/os-june)
- [Venice AI](https://venice.ai/)
- [Hermes Agent](https://hermes-agent.nousresearch.com/)
- [Hermes Agent source](https://github.com/NousResearch/hermes-agent)

ChatGPT can be made more private than its defaults suggest. You can turn off model training, use Temporary Chat, or move work into ChatGPT Business. None of those choices makes the consumer app local, though. Files uploaded from the Mac app are stored in OpenAI's cloud, saved conversations follow OpenAI's retention rules, and Temporary Chats can be kept for up to 30 days for safety.

That may be acceptable for everyday drafting. It may not be the boundary you want for contracts, customer notes, financial documents, source code, or recorded meetings.

This guide compares six alternatives using a stricter question: **what happens to your work after you press send?** If you are looking specifically for native Mac integration, see the separate guide to [ChatGPT desktop alternatives for Mac](https://opensoftware.co/blog/chatgpt-desktop-alternatives-for-mac). If Claude is your current tool, use the [private Claude alternatives](https://opensoftware.co/blog/private-alternatives-to-claude) guide instead.

## How we evaluated the alternatives

This is a documentation-based comparison, not a benchmark of model intelligence. We checked vendor documentation current on July 20, 2026 and evaluated:

- Where saved chats, files, and recordings live.
- Whether content can be used for training.
- How long content may be retained.
- Whether inference is local, zero retention, or ordinary cloud processing.
- Whether administrators get retention, audit, and access controls.
- Whether the product covers real work beyond a chat box.

## Quick answer

| Alternative | Best for | Where history lives | Training default | Main limitation |
|---|---|---|---|---|
| [June](https://opensoftware.co/june) | One private Mac workspace for chat, dictation, meetings, and agent work | On your Mac by default | Default Private models use zero retention and no training | macOS only; default inference still needs internet |
| [Proton Lumo](https://proton.me/lumo) | Encrypted hosted chat | Device plus zero-access encrypted sync | No training | No native Mac app or desktop automation |
| [Duck.ai](https://duck.ai) | Private access to several model families | Not stored by default; optional encrypted sync | No training under provider agreements | OpenAI and Anthropic may cache prompts in memory for up to one hour |
| [Venice](https://venice.ai) | Choosing a privacy level per model | Local browser storage | Private mode is zero retention | Anonymous models may retain prompts upstream |
| [LM Studio](https://lmstudio.ai) | Fully local chat and document work | On your Mac | Local models do not send prompts anywhere | Model quality and speed depend on your hardware |
| [Jan](https://jan.ai) | Open-source local AI | On your Mac | Local use stays local | More setup than a hosted assistant |

There is no universal winner. Hosted privacy services are easier. Local models create a harder data boundary. June sits between them: the workspace and agent run on your Mac, while model calls use private hosted inference by default, with an optional local text-model endpoint for generation and agent work.

## What "private" should mean for work

Privacy claims become confusing because vendors use different words for different controls.

- **Training opt-out** means the provider says it will not use covered content to improve its models. It may still store the content.
- **Zero retention** means the inference provider does not persist the covered prompt or response after processing, subject to documented transient caches and legal or abuse-prevention exceptions.
- **Local history** means your saved conversations live on your device. It does not prove the model itself ran locally.
- **Local inference** means the model runs on hardware you control and the prompt does not need to leave that hardware.
- **Encrypted history** protects saved conversations. A hosted model still needs access to plaintext during inference unless the computation runs inside a verified encrypted environment.

For confidential work, also ask about account records, metering, abuse monitoring, connected tools, web search, and deliberately submitted feedback. "No training" is not the same as "nothing is collected."

## Before switching: make ChatGPT safer

If ChatGPT is already required by your team, start with its available controls.

For individual accounts, turn off **Improve the model for everyone** before entering work content. The change applies to new conversations. Temporary Chat keeps a conversation out of history and model training, but OpenAI may retain a copy for up to 30 days for safety. Files uploaded through the macOS app are stored in the cloud rather than only on the Mac.

ChatGPT Business and Enterprise do not train on business inputs and outputs by default. They are still cloud services with saved workspace data. Business chats remain until a user deletes them. Enterprise administrators can configure a workspace retention policy, subject to OpenAI's available limits.

Those controls are meaningful. They solve a different problem from local storage or zero-retention inference.

## 1. June: best private ChatGPT alternative for an integrated Mac workflow

June combines private chat, push-to-talk dictation into any app, meeting notes without a participant bot, and a local Hermes-based agent in one desktop workspace.

Recordings, transcripts, notes, files, sessions, and agent memory are stored on your Mac by default. When June needs hosted inference, its default Private models route through the open-source June API to zero-retention Venice models. The covered provider does not retain the prompt or use it for training. Anonymous third-party models are optional and may apply different retention rules.

The June API runs inside an attested confidential virtual machine. The public [verification page](https://opensoftware.co/verify) lets you check the June API deployment and source commit. That proof covers the June API layer. It should not be read as proof of every upstream model provider, which is why the model's privacy label still matters.

June also supports an optional OpenAI-compatible local text model for generation and agent work. That can move text inference onto hardware you control. Dictation transcription and meeting-note generation are not fully local by default and still require a network connection.

Zero retention describes prompt content on the default Private inference path. June still keeps the account, billing, capacity, model-selection, request-timing, credit, and error records needed to operate the service. Material you deliberately send in an issue report is retained with that report. Connected tools, websites, and actions introduce their own recipient boundaries.

The current June repository is MIT-licensed and includes both the desktop app and June API. The app supports macOS 14 or later on Apple Silicon and Intel. Capturing system audio for meetings requires macOS 14.2 or later; macOS 14.0 and 14.1 fall back to microphone-only recording.

**Choose June if:** you want one Mac workspace with local history, private hosted inference by default, and an agent that can work with local files and scheduled routines.

**Do not choose June if:** you need Windows today, require all speech processing to stay offline, or want a team knowledge base stored centrally in the cloud.

**Pricing:** Free, Pro at $20/month, and Max at $100/month. Scheduled routines are available on Pro and above. Pricing changes usage and model access, not the privacy standard of the default Private tier.

## 2. Proton Lumo: best encrypted hosted chat

Lumo is Proton's privacy-focused web and mobile assistant. It runs open models on servers controlled by Proton rather than sending prompts to third-party model providers.

Proton says prompts are erased after processing, are not used for training, and do not appear in prompt or response logs. Saved history is protected with zero-access encryption, so Proton stores encrypted history but cannot decrypt it after it has been saved. The service still processes plaintext on Proton-controlled inference servers for the moment required to generate a response. Account, payment, security, and service records are separate from prompt-content logs.

That architecture is strong for private hosted chat. It is not an offline model, a native Mac app, a system-wide dictation tool, or a desktop agent.

**Choose Lumo if:** your primary need is private writing, summarization, and question answering in a browser.

**Do not choose Lumo if:** you need a frontier model from a specific provider, Mac automation, meeting capture, or local file workflows beyond its supported integrations.

## 3. Duck.ai: best private access to multiple model families

Duck.ai acts as a privacy layer between you and providers including OpenAI, Anthropic, Mistral, Azure, and Tinfoil. DuckDuckGo removes identifying metadata before sending a request and says its provider agreements prohibit training and require zero data retention.

The details vary by model. OpenAI and Anthropic may hold prompt caches in memory for up to one hour, and Anthropic has limited legal and abuse-prevention exceptions. Tinfoil-hosted models add a Trusted Execution Environment that DuckDuckGo labels "zero provider visibility." Uploaded files and images are scanned for child sexual abuse material outside the encrypted Tinfoil path and may be retained and reported if flagged.

Chats are not stored by default. Optional Sync and Backup stores them in end-to-end encrypted form.

**Choose Duck.ai if:** you want to compare several model families without giving each provider your identity or direct account.

**Do not choose Duck.ai if:** you need a native desktop workspace, offline use, persistent local agents, or one uniform guarantee across every available model.

## 4. Venice: best if you want to choose the privacy boundary per chat

Venice stores conversation history in the browser and offers four privacy modes.

- **Anonymous:** Venice hides your identity from a frontier provider, but the provider may store the prompt.
- **Private:** the default for supported models, using Venice-controlled GPUs or zero-retention partners.
- **TEE:** inference runs in a hardware-isolated environment with remote attestation.
- **E2EE:** the prompt is encrypted on your device and decrypted only inside a verified TEE.

E2EE trades away some features. It currently does not support web search, memory, file upload, or function calling. Venice also collects limited product and account event data even though it does not store prompt content on its servers.

**Choose Venice if:** you want hosted private inference and understand the model-by-model privacy labels.

**Do not choose Venice if:** you expect every frontier model in the catalog to have the same retention guarantee or need a native Mac desktop agent.

## 5. LM Studio: best polished local model workspace

LM Studio can run downloaded models entirely offline. Local chats, document retrieval, and its OpenAI-compatible local server stay on the machine. Searching for and downloading models, checking for updates, web search, and optional cloud models require network access.

The tradeoff is hardware. A smaller local model can be private and fast while still falling short of a large hosted model on difficult analysis, long documents, or tool use. You also own model selection, storage, updates, and backups.

LM Studio now offers cloud models and web search under zero-retention terms. Selecting those features changes the system from local inference to hosted inference, even though the interface stays the same.

**Choose LM Studio if:** your non-negotiable requirement is that ordinary chats and documents can remain on your Mac.

**Do not choose LM Studio if:** you want a turnkey meeting-notes and dictation workflow or do not want to manage model files and memory constraints.

## 6. Jan: best open-source local ChatGPT-style app

Jan is an Apache 2.0 licensed desktop application for macOS, Windows, and Linux. With a local model, it works offline, stores conversations and settings locally, and does not collect telemetry unless you allow it.

Jan can also connect to cloud providers and external tools. Once you select a cloud model or networked integration, that provider's privacy terms apply. Open source does not make an external API local.

On Mac, Jan currently requires macOS 13.6 or later and Apple Silicon. Model size determines the practical memory requirement.

**Choose Jan if:** you want an auditable, no-account local assistant and are comfortable choosing open models.

**Do not choose Jan if:** you need the quality of a specific frontier model without sending prompts to that provider, or want automatic meeting and dictation workflows.

## What about Claude, Gemini, Copilot, and Perplexity?

These can be appropriate for organizational work, but their strongest privacy posture comes from plan terms and administration rather than local or zero-retention architecture.

| Service | Stronger work configuration | Important limitation |
|---|---|---|
| Claude | Team or Enterprise content is not used for model training by default | Saved chats remain in Anthropic's cloud until deleted or an enterprise retention rule applies |
| Gemini | Qualifying Google Workspace content is not used to train models outside Workspace without permission | Consumer Gemini has separate activity and retention controls |
| Microsoft 365 Copilot | Enterprise Data Protection prevents prompts and responses from training foundation models | Prompts and responses are logged and governed through Microsoft Purview |
| Perplexity | Enterprise data is not used for training and third-party providers use zero-retention terms | Consumer AI data retention is enabled by default unless you opt out |

For regulated work, "not used for training" is only one control. Your organization may also need retention policies, audit logs, access controls, data residency, and a contract. A privacy-first consumer product is not automatically a compliance program.

## Requirements matrix for professional work

| Requirement | Shortlist | What to verify before rollout |
|---|---|---|
| Contract review that must stay on one Mac | LM Studio or Jan with a local model | Model files, retrieval, tools, backups, and web search all remain local |
| Confidential chat with hosted inference | Lumo, Duck.ai, Venice Private/TEE/E2EE, or June Private models | Exact model badge, retention exceptions, abuse handling, and account metadata |
| Meeting recordings and transcripts | June | Recording consent, system-audio support, inference path, and local backup policy |
| Centralized company governance | ChatGPT Enterprise, Claude Enterprise, Gemini for Workspace, or Microsoft 365 Copilot | Contract terms, admin retention, eDiscovery, residency, and incident response |
| Local agent acting on files | June, Jan, or a local-model stack | Approval model, sandbox boundary, connected tools, and whether the selected model is local |

## Decision guide

Choose based on the boundary you actually need:

1. **Everything must remain on hardware you control:** use LM Studio or Jan with a local model and local tools.
2. **You want private hosted chat with encrypted history:** use Proton Lumo.
3. **You want several frontier providers behind a privacy proxy:** use Duck.ai, checking the label and exceptions for each model.
4. **You want hosted inference with selectable TEE or E2EE modes:** use Venice.
5. **You want chat, dictation, meetings, and local agent workflows in one Mac app:** use June.
6. **Your employer requires centralized governance:** evaluate the business or enterprise plan of the provider your organization already manages.

## Sources and verification

Product policies change. This article was checked on July 20, 2026 against the vendors' primary documentation:

- [OpenAI data controls](https://help.openai.com/en/articles/7730893-chatgpt-data-controls-faq) and [Mac app retention](https://help.openai.com/en/articles/9268871-how-is-data-retained-in-the-macos-app)
- [OpenAI business data commitments](https://openai.com/business-data/)
- [OpenAI chat and file retention](https://help.openai.com/en/articles/8983778-chat-and-file-retention-policies-in-chatgpt)
- [Proton Lumo privacy](https://proton.me/support/lumo-privacy)
- [Duck.ai privacy details and provider exceptions](https://duckduckgo.com/duckduckgo-help-pages/duckai/ai-chat-privacy)
- [Venice privacy modes](https://venice.ai/privacy)
- [Venice TEE and E2EE feature limits](https://docs.venice.ai/guides/features/tee-e2ee-models)
- [LM Studio offline operation](https://lmstudio.ai/docs/app/offline) and [app privacy](https://lmstudio.ai/app-privacy)
- [Jan privacy](https://www.jan.ai/docs/desktop/privacy) and [Mac requirements](https://www.jan.ai/docs/desktop/install/mac)
- [June privacy and product FAQ](https://opensoftware.co/june/faq) and [June API verification](https://opensoftware.co/verify)