Nothing privileged leaves by accident. And you can prove it.

Because the cost of one accident has gone up and the odds haven't gone down. The human element is in 62% of breaches (Verizon DBIR 2026), and you don't get to un-send a disclosure. Meanwhile malpractice carriers and corporate clients are beginning to ask for proof of controls, and your staff are already pasting case facts into AI tools. The firms that get ahead of this do it before the near-miss, not after.

Yes. DataGuard proposes every removal and cites the authority your policy names. Your reviewer approves, edits, or overrides before anything is sent, one click each. Judgment stays with the lawyer, and both the engine's proposals and every human decision are logged, so the record is complete either way.

Purview is built to flag violations and stop shares. In the firm deployments we have seen, its DLP blocks the share rather than redacting the file. DataGuard proposes removals so the document can go out with the rest intact, instead of stopping the send, and your reviewer approves before it leaves. The two tools serve different purposes.

Yes. That's the internal-access layer, live today. You define the screen, and the same policy that governs what leaves the firm enforces it on internal access: staff see only the matters their role allows, and access attempts are logged. Setting the screen correctly stays with the firm.

Your team is already using AI, so the answer is to give them a safe way to do it rather than a ban. The AI Vault builds a synthetic mirror of a matter: names, clients, emails and identifiers are replaced with a consistent stand-in, and you connect Claude, ChatGPT or Copilot to the Vault so the model reads the mirror instead of the real file. The same value maps to the same stand-in across every document, so the assistant can still reason across the whole matter, and results map back to your real values on your side, when a person reviews them. To be precise about what this is: it is a vault the AI reads from, not something that intercepts a paste in a browser window.

The document content is analyzed in memory and discarded. What persists is the record of what was proposed, what was approved, and by whom, never the sensitive values themselves, and none of it is used for training. Our detection engine runs only on Sidian's own private models, so testing a file does not put a privileged document in a third party's hands. Your own assistants read the synthetic mirror, never the real file.

Small firms are exactly who this was made for. You carry the same client data and the same duties as a large firm, with less margin to absorb a hit and no enterprise IT team. DataGuard is built to SOC 2 standards, with Type II in progress, and it deploys in minutes with no configuration project.

Connected in minutes, watching the same day. One admin consent in the console you already run, no install and no new login. You turn on enforcement once you have seen what it catches on your own files.

Your CMS removes text if you tell it to. DataGuard flags candidates, cites the authority your policy names, and keeps a record of what your reviewer decided. Your files stay exactly where they are, in Clio, SharePoint, wherever your firm already keeps them. DataGuard reads and checks; it never becomes a second place your documents live.