99 private AI chat products, but privacy comes in four different architectures

Asked:
every private ai chat product

A broad live-web scan on 2 September 2026 — 32 search queries across official product, help, privacy and docs pages, repositories and roundups — surfaced 99 privacy-oriented AI chat products or materially distinct plan variants. “Every” cannot be guaranteed: the market and the open-source ecosystem change continuously, so this is a broad discovered catalog, not an exhaustive registry.

One dot per product — four ways of being “private”

Local/offline — inference stays on the device Self-hosted/local — you run the infrastructure Hosted privacy-focused — provider promises + technical measures Enterprise private — no-training pledge + governance controls

What each architecture actually protects

Local/offline · 31

Models run on your own machine; prompts need never leave it. But “local-capable” is not a guarantee — enabling cloud model providers, sync, web search, connectors or telemetry can send data off-device.

Self-hosted/local · 16

You deploy the chat stack on infrastructure you control. Privacy is as strong as your operations. Many entries are small repository projects — assess maintenance and security before deployment.

Hosted privacy-focused · 9

Cloud services built around no-logs, zero or short retention, anonymizing proxies, or client-side encrypted history. You are trusting provider promises and technical measures, not your own hardware.

Enterprise private · 43

Business plans that promise no training on your data plus retention controls, encryption, compliance and admin governance. Privacy for the organization; the provider still processes the data.

Read the fine print“Not used for training” does not mean “not retained” — several enterprise plans keep history for months or years by default. And none of these claims are certifications: nothing here is independently verified privacy. Entries mix consumer apps, open-source projects and enterprise plans, so rows are not all direct substitutes for one another.

Findings

Enterprise-private plans are the largest group (43 of 99) yet come from just 9 providers — e.g. Google’s Gemini keeps conversation history for 18 months by default unless an admin changes it. support.google.com
Only 9 hosted consumer products lead with hard technical privacy — Duck.ai deletes prompts and responses immediately after generating a reply and prohibits training use. duckduckgo.com
47 of 99 entries (local/offline plus self-hosted) remove the provider entirely — from mature projects like GPT4All to one-file repositories. docs.gpt4all.io
Hosted privacy can go beyond “trust us”: Proton’s Lumo keeps no server-side logs and stores chats so they can only be decrypted on your device. proton.me

The full catalog

ProductProviderPrivacy claim / training-use statementSource

Method: broad live-web scan on 2026-09-02 using 32 diverse web-search queries; official product, help, privacy and docs pages plus repositories and roundups were reviewed, then extracted, normalized and screened into 99 products or materially distinct plan variants across four privacy architectures. Category counts are taken from the catalog’s own aggregates. Blank fields mean unknown, not “no”. Claims are quoted or condensed from vendor pages and are not independently verified; deployment, pricing and platform details were cut for space where absent from source pages. Not exhaustive — the market changes continuously.

This report was generated automatically by Keenable SELECT at a user's request, from publicly available web sources linked herein. Keenable does not review, verify, or endorse its contents and makes no representation as to accuracy, completeness, or timeliness; AI-based extraction may contain errors. Nothing in this report is investment, legal, financial, or other professional advice. All trademarks and referenced content remain the property of their respective owners; no affiliation or endorsement is implied. To report an error, rights concern, or request removal: legal@keenable.ai.

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