Redact sensitive data
in AI prompts
Central AI filters employee prompts to detect and redact confidential data before it can leave your organisation
macOS and Windows
Protects the AI tools your employees already use
Your team is pasting more than you think into AI.
Every department now has a chat window open. Sensitive data walks out one prompt at a time — and your existing DLP never sees it.
Draft a renewal email to john.smith@acme.com referencing contract #MSA-2241 at $248,000 ARR, expiring March 14.
Customer PII, contract IDs and ARR pasted into a public LLM.
Summarize Q3 board deck: revenue $48.2M, gross margin 71.4%, churn 4.8%, runway 19 months.
Unreleased financials uploaded for a one-page summary.
Compare our roadmap (Project Helios, ship Q1 2026) against competitor X's public docs.
Codenames and ship dates leak into model training pipelines.
Rewrite this PIP for Maria Chen, SWE II, salary $182,000, manager D. Patel, case HR-8821.
Employee records and case files dropped into a chat box.
Developers leak secrets and source without meaning to.
A copy-paste into Copilot Chat or ChatGPT can ship an API key, a customer record, or your entire .env file to a third-party model in a single keystroke.
> Help me debug why prod auth is failing. Here is the snippet: const stripe = new Stripe( "sk_live_51N8aZkH...4xQwerty" ); const db = postgres( "postgres://app:Hunter2!@db.prod.acme.io:5432/prod" ); // JWT we issued to user 8821 const token = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."; // Stack trace contained: // email=r.gupta@acme-customer.com // internal=https://billing.internal.acme.io/v2/charges
A typical "help me debug" prompt — six different secret types in ten lines.
We redact only what's sensitive — the prompt stays useful.
Inline, in real time, in the same chat. Sensitive spans are swapped for typed placeholders so the model sees structure, not secrets — and your team never breaks flow.
Draft a follow-up email to john.smith@acme.com from Maria Chen about invoice #INV-8842 for $48,200, due Friday.
Reference the dashboard at https://billing.internal.acme.io/inv/8842 and use API key sk_live_51N8aZkH4xQwerty if you need to pull line items.
Draft a follow-up email to <CUSTOMER_EMAIL_1> from <PERSON_1> about invoice <INVOICE_ID_1> for <FINANCIAL_1>, due <DATE_1>.
Reference the dashboard at <INTERNAL_URL_1> and use API key <SECRET_1> if you need to pull line items.
What gets swapped, and what the model sees instead
Detected → PlaceholderThe model's reply is automatically re-hydrated with the real values, in-line.
Tokens keep shape and type so the model still produces useful, structured output.
Works in ChatGPT, Claude, Gemini, Copilot, Cursor — no plugin for the end user.
The risk gap
What enterprises lose with unmanaged AI use
Employees are already using AI. Without a filtering layer, every prompt, upload, and generated response can become a data exposure event.
| Capability | With Central AI | Without |
|---|---|---|
| Prompts scanned before submission | ||
| PII, PHI, PCI, and secrets detected | ||
| Sensitive text redacted automatically | ||
| Uploads inspected for confidential data | ||
| Policy-based allow, warn, or block controls | ||
| Employee AI usage visibility | ||
| Audit trail for compliance reviews | ||
| Safe AI access without blanket bans |
The blind spots
Why enterprise AI use needs a filter
Shadow AI is invisible
Employees paste customer records, contracts, source code, and spreadsheets into AI tools before security teams ever see it.
Files bypass policy
Uploads can contain hidden PII, credentials, financial data, or regulated content that standard browser controls miss.
Policies are hard to enforce
Acceptable-use docs do not stop risky prompts in real time or adapt to different teams, data types, and destinations.
No audit trail
When a leak is suspected, teams lack the prompt history, decision logs, and redaction records needed to investigate.
How it works
Let employees use AI without leaking data
What you get
Enterprise controls for safe AI adoption
Sensitive data detection
Find PII, PHI, PCI, source code, contracts, and confidential terms inside prompts, pasted text, and uploads.
Secrets protection
Catch API keys, tokens, credentials, private certificates, and internal endpoints before they reach external AI tools.
File inspection
Scan documents, spreadsheets, and attachments for regulated or proprietary information before employees submit them.
Real-time redaction
Automatically remove risky values while preserving enough context for employees to keep working safely.
Policy controls
Set rules by team, data type, tool, destination, sensitivity level, and workflow approval requirements.
Audit logs
Keep searchable records of detections, redactions, warnings, blocks, and approvals for compliance reviews.
AI tool coverage
Protect usage across popular AI assistants, internal copilots, browser workflows, and approved enterprise tools.
Risk reporting
See adoption trends, risky departments, blocked data classes, and policy performance from one security dashboard.
Who it's for
Built for enterprises adopting AI safely
Security teams enabling AI
Reduce data-loss risk while giving employees a safe path to use approved AI tools at work.
IT leaders managing access
Apply consistent filtering, policy controls, and visibility across departments, tools, and user groups.
Compliance and risk teams
Maintain evidence of policy enforcement, redaction decisions, and sensitive-data handling for audits.
Ready to make enterprise AI safe?
Give employees the AI tools they want with the data protection your enterprise requires.