Private AI for teams: keep your company's data out of model training

It depends on the tool. Many consumer AI products may retain prompts and uploaded files and use them to improve or train future models unless you opt out. The risk is that confidential material, contracts, customer records, internal strategy, can be absorbed into a model you do not control and surface elsewhere.

The safe posture is zero data retention with the model provider: the provider processes your request, returns an answer, and keeps nothing for training. Tatsulok sends every chat request only to model providers under zero data retention, so your questions and the passages sent with them are neither kept by those providers nor used for training. Voice input, web search, document extraction and search reranking run under their own providers' terms, listed in our privacy policy.

The privacy worry is widespread and well-founded: Cyberhaven's analysis of workplace AI use found that roughly 11% of what employees paste into ChatGPT is sensitive company data, exactly the kind of leak a private, access-controlled workspace is designed to prevent.

Privacy is mechanics, not a slogan. A genuinely private AI tool does three concrete things. First, it guarantees your content is never used for model training. Second, it encrypts your data in transit and at rest, and keeps it private by default rather than shared or public. Third, it gives you real control: you decide who can see each document, per team or per person, and you can delete content at any time.

If a tool cannot describe each of these in plain terms, treat the privacy claim as unverified.

Confidentiality inside a team is an access-control problem. The answer is not to stop sharing, but to share precisely. Each document should have explicit access, granted to a specific team or a specific person, so a file is visible only to those who need it.

When someone leaves a project or the work ends, revoke their access and delete what is no longer needed. In Tatsulok, you control access per team and per person.

Confidential knowledge should outlast the people who created it. When answers live in individuals' private chat histories, that knowledge walks out the door when they do, and you have no way to revoke it.

A private team library fixes this. Because documents live in one access-controlled place rather than scattered prompts, institutional knowledge keeps accumulating, and you can revoke a departing person's access without losing what the team built. Continuity and control are the same mechanism.

Tatsulok keeps your data private by default, and your workspace is never sent to training datasets. Your files are encrypted at rest, you control who can access them, per team or per person, and you can delete anything at any time.

Just as important, answers about your files come from your own documents, and each one is cited to the exact source passage, with a highlighted preview and a link back to the original, so you can verify where every statement came from. Tatsulok reads PDF, Word, Excel and PowerPoint files and works in English and Japanese.