AI app for it and development · no coding needed
Sensitive prompt and document exposure guard
Reduce sensitive data exposure in employee AI use while keeping the tools employees already use.
Made for: Security, IT and compliance teams in regulated organizations whose employees send prompts and documents to third-party AI tools
What it does for you
The problem
Employees paste credentials, personal data and confidential documents into external AI tools, and administrators cannot see what leaves the organization.
What it gives you
Flagged categories, synthetic replacements and tokenized values with a metadata-only admin view
What you give it
Prompt samplesdocument typespolicy categoriesbrowseragent configurations
Build your own version of Sequirly, PrivacyPal and more
One app with what these 3 AI tools do, yours to keep and change: Sequirly, PrivacyPal, Astra.
Everything these tools do, in one app
- Real-time sensitive data scanning Scans prompts and files as they are entered to detect API keys, credentials, and personal data before submission.Found in Sequirly
- Document upload scanning Checks uploaded contracts, spreadsheets, and other files for sensitive items before they are sent.Found in Sequirly
- Local browser processing Processes scanned content entirely in the browser so raw data never leaves the user's device.Found in Sequirly
- Metadata-only admin dashboard Reports flagged categories to administrators without exposing the actual content of prompts or files.Found in Sequirly
- Synthetic data replacement Replaces sensitive values with synthetic equivalents while preserving the original context and structure for the AI model.Found in PrivacyPal
- Local data reconstitution Restores original data in the browser so users see a natural experience while external services only see synthetic data.Found in PrivacyPal
- Prompt audit logs Records prompts sent to third-party models to provide governance visibility and identify high-risk activity.Found in PrivacyPal, Astra
- Browser extension deployment Installs as a browser extension that operates in real time between the user and the AI model without requiring internal LLM hosting.Found in PrivacyPal, Sequirly
- Pre-prompt tokenization Tokenizes sensitive data such as PHI, PCI, and PII before it reaches the model so raw values are never included in prompts.Found in Astra
- Token resolution at execution Resolves tokens to real values only at the moment of action, with real values held in a secure vault and not written to logs.Found in Astra
- Audit trail without raw data Records tokens, actions, timestamps, and authorization events without storing raw sensitive data.Found in Astra
- Agent framework compatibility Works with existing agent frameworks and requires minimal integration effort, advertised as two lines of code.Found in Astra
- Reveal logging Logs when a token is revealed while keeping the revealed value separate and access-controlled.Found in Astra
How it works, step by step
- Scan prompts in real time for API keys, credentials and personal data
- Scan uploaded contracts, spreadsheets and files before submission
- Process scanned content locally in the browser
- Report flagged categories to administrators without exposing content
- Replace sensitive values with synthetic equivalents
- Preserve original context and structure for the model
- Reconstitute original data locally in the browser
- Record prompts sent to third-party models for governance
- Tokenize PHI, PCI and PII before prompts reach the model
- Resolve tokens to real values only at execution
- Hold real values in a secure vault outside logs
- Record tokens, actions, timestamps and authorization events
- Log token reveals with separate access control
- Support existing agent frameworks with minimal integration
- Compare the reviewed result with the recorded baseline and value assumptions
- Export a versioned flagged categories, synthetic replacements and tokenized values record with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Sensitive prompt and document exposure guard with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Sensitive prompt and document exposure guard with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links4 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare27 KB
- prompt-vps.mdThe same build on your own server (Docker)27 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria14 KB
- demo/index.htmlThe working demo on sample data198 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce sensitive data exposure in employee AI use while keeping the tools employees already use. For security, IT and compliance teams in regulated organizations, convert prompts, uploaded documents, browser sessions and existing agent calls into flagged categories, synthetic replacements and tokenized values with a metadata-only admin view. The benefit is a testable hypothesis, measured through flagged items per reviewed session, confirmed exposure incidents and reviewer time per alert; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect prompt samples, document types, policy categories, browser and agent configurations, then follow this sequence: 1. Scan prompts in real time for API keys, credentials and personal data. 2. Scan uploaded contracts, spreadsheets and files before submission. 3. Replace sensitive values with synthetic equivalents. 4. Tokenize PHI, PCI and PII before prompts reach the model. Resolve uncertain cases with qualified reviewers, approve flagged categories, synthetic replacements and tokenized values, and measure flagged items per reviewed session and confirmed exposure incidents against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated scanning, replacement and tokenization modules. Use deterministic code for pattern matching, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Browser-local processing and a secure vault; final policy decisions and incident classification remain with security reviewers. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve employee privacy, source attribution, data classification accuracy and usage permissions. Security reviewers approve policy changes and incident scope. One browser, one agent framework and one policy category set; final policy decisions and incident classification remain with security reviewers. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One browser, one agent framework and one policy category set; final policy decisions and incident classification remain with security reviewers. Implement one approved input format, a bounded representative case set and the first two task modules: scan prompts in real time for API keys, credentials and personal data; scan uploaded contracts, spreadsheets and files before submission. Support the remaining modules with operator review: replace sensitive values with synthetic equivalents; tokenize PHI, PCI and PII before prompts reach the model. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Employee browsers, existing agent frameworks, identity providers and permitted AI tool endpoints. Cloud policy storage, audit log export and security information and event management destinations. Start with file exchange and validate destination specifications before promising direct enforcement. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Policy and category setup, Live prompt and document review, Admin exposure dashboard. Use a list of monitored sessions, a central review panel showing flagged categories and synthetic replacements, and a right-hand panel for policy rules, token vault status and audit events. Let reviewers compare original and synthetic context side by side where permitted. Display allowed, flagged, blocked and revealed states. Provide a metadata-only admin view with no raw content. Make the task-specific outcome flagged categories, synthetic replacements and tokenized values visible beside its evidence, review state and value baseline.
