AI app for it and development · no coding needed
Source-linked AI use governance console
Reduce the risk and review effort of everyday AI use while keeping a defensible record.
Made for: IT, security and compliance teams in mid-sized organizations whose staff use AI tools
What it does for you
The problem
Staff paste confidential data into AI tools, outputs go unchecked, and no one can show what was sent, what came back or who approved it.
What it gives you
Source-linked AI use record with named-owner approval
What you give it
Permitted promptsmodel outputsfilter rulesreviewer decisions
Build your own version of GPTGuard, Stableoutput and more
One app with what these 7 AI tools do, yours to keep and change: GPTGuard, Stableoutput, AgentSea, ZeroTrusted.ai, AI Eraser, Serendipity, Vibespace.
Everything these tools do, in one app
- AI content generation Generates text or ideas automatically from user input.Found in Stableoutput, Serendipity
- Sensitive data redaction Automatically detects and removes or masks personal and confidential information from prompts.Found in ZeroTrusted.ai, AI Eraser
- Real-time content monitoring Continuously scans AI-generated text to flag harmful or misleading content.Found in GPTGuard
- Customizable filters and alerts Lets users set specific filters and alert preferences for content oversight.Found in GPTGuard
- Reporting dashboard Provides a dashboard to track flagged instances and trends over time.Found in GPTGuard
- Multi-model access Allows users to interact with multiple AI models through a single interface.Found in AgentSea, ZeroTrusted.ai
- Privacy protection mode Runs chats in a secure mode that prevents data from entering training pipelines or being exposed.Found in AgentSea, ZeroTrusted.ai
- Agent marketplace Offers a collection of community-built AI agents for various tasks.Found in AgentSea
- Social media search Integrates search across social platforms like X, Reddit, Google, and YouTube.Found in AgentSea
- Image generation Generates images within the chat environment.Found in AgentSea
- Conversation context retention Maintains memory and context across multiple chats.Found in AgentSea
- Data fictionalization Replaces real data with fictional values while preserving context for accurate AI responses.Found in ZeroTrusted.ai
- LLM reliability module Runs queries through multiple LLMs and selects the best response to improve accuracy.Found in ZeroTrusted.ai
- Local data processing Performs redaction or processing entirely on the user's device without sending data externally.Found in AI Eraser
- Browser extension integration Integrates as a browser extension for easy access.Found in AI Eraser
- Template library Provides pre-made templates for different content types like blogs, ads, and emails.Found in Stableoutput
- Real-time editing suggestions Offers suggestions to improve grammar and readability as you write.Found in Stableoutput
- Multi-agent collaboration Enables multiple AI agents to communicate and coordinate tasks via channels and direct messages.Found in Vibespace
- Sandboxed runtime Runs agents in an isolated virtual machine to keep activity separate from the host system.Found in Vibespace
- Conflict resolution Uses a leader agent and worktree strategies to manage merges and resolve conflicts between agents.Found in Vibespace
- Real-time collaboration Allows team members to collaborate in real time on content or projects.Found in Serendipity
How it works, step by step
- Generate text or ideas from user input
- Detect and mask personal and confidential data in prompts
- Scan AI-generated text for harmful or misleading content
- Apply user-defined filters and alert preferences
- Track flagged instances and trends in a dashboard
- Route prompts to multiple AI models from one interface
- Run chats in a privacy mode that blocks training use and exposure
- Offer a catalogue of community-built agents
- Search social platforms for context
- Generate images inside the chat environment
- Retain conversation context across chats
- Replace real data with fictional values while preserving context
- Compare responses from several models and select the best
- Redact or process data locally on the device
- Provide a browser extension for access
- Supply pre-made templates for common content types
- Suggest grammar and readability edits as users write
- Let multiple agents coordinate through channels and direct messages
- Run agents in an isolated virtual machine
- Resolve agent conflicts with a leader agent and worktree merges
- Let team members collaborate on content in real time
- Capture corrections and named-owner approval before consequential use
- Export a versioned source-linked AI use 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 Source-linked AI use governance console 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 Source-linked AI use governance console 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 Cloudflare24 KB
- prompt-vps.mdThe same build on your own server (Docker)24 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria11 KB
- demo/index.htmlThe working demo on sample data196 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 the risk and review effort of everyday AI use while keeping a defensible record. For IT, security and compliance teams in mid-sized organizations whose staff use AI tools, convert permitted prompts, model outputs, filter rules and reviewer decisions into a source-linked AI use record with named-owner approval. The benefit is a testable hypothesis, measured through reviewed AI interactions per compliance hour and policy incidents after deployment; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect permitted prompts, model outputs, filter rules and reviewer decisions, then follow this sequence: 1. Generate text or ideas from user input. 2. Detect and mask personal and confidential data in prompts. 3. Scan AI-generated text for harmful or misleading content. 4. Apply user-defined filters and alert preferences. 5. Track flagged instances and trends in a dashboard. Resolve uncertain cases with qualified reviewers, approve a source-linked AI use record with named-owner approval, and measure reviewed AI interactions per compliance hour and policy incidents after deployment against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for redaction rules, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One approved model set and filter configuration; final policy and disclosure decisions remain with the compliance owner. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve data subject rights, source attribution, redaction accuracy and usage permissions. Compliance owners approve policy changes and disclosure scope. One approved model set and filter configuration; final policy and disclosure decisions remain with the compliance owner. 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 approved model set and filter configuration; final policy and disclosure decisions remain with the compliance owner. Implement one approved input format, a bounded representative case set and the first two task modules: detect and mask personal and confidential data in prompts; scan AI-generated text for harmful or misleading content. Support the remaining modules with operator review. 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
Organization identity providers, model APIs, browser extension endpoints and audit export destinations. Start with file exchange and validate destination specifications before promising direct integration. 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 filter setup, Live interaction review, Reporting and audit export. Use a queue of flagged interactions, a large central view of the prompt, redacted version, model output and source references, and a right-hand panel for filters, alerts and reviewer comments. Let reviewers compare original and redacted text side by side. Display draft, changes requested and approved states. Provide a client-facing audit link with comments anchored to the relevant interaction. Make the task-specific outcome a source-linked AI use record with named-owner approval visible beside its evidence, review state and value baseline.
