Privacy & tools: the private AI guide

AI where you can reduce what you disclose before asking. With Privacy Shield on for a supported text flow, detected identifiers are replaced with placeholders before the question reaches a model, and restored in the answer you read.

Privacy Shield adds data minimisation before supported model calls, replacing detected personal identifiers. It reduces direct identifiers submitted; it doesn't replace your own organization's rules or a provider's privacy terms.

When enabled on a supported text flow, it detects personal details in your question, replaces them with placeholders before the models see anything, then restores them locally where supported. Detection is automated and can miss unusual or contextual identifiers.

No. Privacy Shield currently covers supported text flows. Images, attachments and some tools may need separate handling — avoid including sensitive details that aren't needed for the request.

Yes. Privacy Shield is available at no extra cost on all plans, including Free, on iPhone and the web — no card required to start.

Ask each model the same question and line up the answers. Side-by-side tools show them in parallel, but you still judge. A consensus engine like Satcove compares the six and returns one verdict with an agreement score, so you don't reconcile them by hand.

Don't pick by fluency — compare the substance, inspect where models split, verify consequential claims, then arbitrate the tradeoffs into a practical next step. Satcove does this across six independent answers.

Not quite. A multi-LLM platform gives you access to several models, usually one at a time or side by side. A consensus engine queries them together and synthesizes one verdict — comparison is the input, the verdict is the output.

Yes. Satcove's free plan includes 3 multi-model queries a week on iPhone and the web, no card required.

Give the models the same question and context, then compare their conclusions, sources, assumptions and disagreements. Satcove queries the panel in parallel and synthesizes the useful differences into one structured verdict.

Each app's memory is per-app and per-conversation, so nothing about one project survives into the tab where you keep another. Every switch is a cold start. The fix isn't discipline — it's a workspace that holds each project's context and feeds it to whichever model you ask.

Because it never saw the earlier conversation: not your files, not your constraints, not the options you already rejected. It just repeats them back to you. Asking several models against one shared project memory means the second opinion builds on the first instead of restarting it.

Each app's memory is private to that app — there's no shared layer between them by default. The context isn't lost by accident; it simply never left the app you typed it into.

Only if each model has its own separate memory. A shared workspace memory lets you ask a different model the same question without re-explaining the project first.

Yes — Cove Memory is shared across the models in a conversation, so switching which model answers doesn't mean starting over.

The fix is a shared project workspace instead of per-person, per-app chat history. When the project context — files, constraints, decisions already made — lives in one place every model reads from, a teammate moving from one AI to another starts from the same state, not a blank prompt. Cove Memory holds that shared context so the switch costs nothing.

Stop treating each AI tool as its own silo. A workspace that carries the project context across models means the second tool already has what the first one was told — no rebuilding the frame, no re-pasting the spec. The switch becomes a change of model, not a cold start.