Inline detection where people type.
The BeeSensible extension lives inside the apps your team already uses. When someone types or pastes sensitive data, we highlight it in context, before the message leaves the page.
Detection runs in
ChatGPT 
Claude 
Gemini 
Copilot 
Gmail 
Outlook 
Slack 
Teams Two surfaces, one experience.
BeeSensible adapts to the host app (AI assistants, email, chat) but the detection model and side panel stay consistent everywhere.
ChatGPT
In a live AI chat, BeeSensible highlights regulated data before the prompt is sent and explains the risk in plain language.
Gmail
In email, the same panel surfaces customer identifiers, financial data, and credentials before the draft becomes a forwarded thread.
Built like spell-check, not like a firewall.
Inline highlights
Sensitive data underlined where it appears.
Names, IBANs, BSNs, phone numbers, secrets. People see exactly what's flagged in the message they're writing, not in a separate review queue.
Side panel
A clear list of what was found.
The panel groups every detection by category and severity, so the writer can scan and act in seconds instead of re-reading the whole draft.
User actions
Mask, replace, or remove. Or send anyway.
Three quick actions handle the data without rewriting the message. The user always stays in control; BeeSensible never blocks send.
Privacy by default
Detection runs in the browser session.
Message content isn't shipped to a search index or stored as logs. The dashboards see counts and patterns, never the words people typed.
In the moment
Three clear actions, then the message is theirs again.
01
Review the highlight
Underlines and the side panel show exactly which names, IDs, credentials, or financial details need attention.
02
Choose an action
Mask, replace, or remove the sensitive value while keeping the draft readable. One click, no copy-paste.
03
Send with intent
If the data belongs there, the user can continue deliberately. The product is a safety net, not a blocker.
The product does not decide for the user.
BeeSensible shows the issue and offers clear actions. The employee stays in control of the message.
Roll out the extension to the apps that matter most.
Start with the AI tools and inboxes where exposure is highest. Tune detection per app from the admin dashboard.