AI app for it and development · no coding needed
Agent action control and audit portal
Reduce unauthorized or unreviewed agent actions while keeping a complete record of what each agent touched.
Made for: Platform, security and IT operations teams running AI agents that connect to internal apps, tools and data
What it does for you
The problem
Agents act across connected systems without a single place to authorize each action, review what happened or stop a bad run.
What it gives you
Operator-approved decision record linked to each executed action
What you give it
Agent action requestsconnector definitionsidentity datapolicy rules
Build your own version of Venn.ai, Kastra and more
One app with what these 10 AI tools do, yours to keep and change: Venn.ai, Kastra, Portia AI, Merge Agent Handler, Mighty, Jentic Mini, Permit AI Access Control, CtrlAI, Multi-Agent Builder, Graft AI.
Everything these tools do, in one app
- Agent action authorization Evaluates each agent action against rules and returns an allow or deny decision before it runs.Found in Kastra, CtrlAI, Venn.ai and 1 more
- Activity audit logs Records every agent action with details of what was touched and whether it was allowed or blocked.Found in Venn.ai, Kastra, Portia AI and 6 more
- Human-in-the-loop approval Routes actions that need a person's decision to a human for approval before continuing.Found in Kastra, Portia AI, Graft AI
- Cross-agent compatibility Works with multiple AI agents or frameworks so the same controls apply without rebuilding for each.Found in Venn.ai, Kastra, CtrlAI
- No-code setup Lets users connect and configure agent controls without writing code.Found in Venn.ai, Multi-Agent Builder
- Credential management Stores and injects credentials securely so agents can access tools without seeing secrets.Found in Merge Agent Handler, Mighty, Jentic Mini
- Connector generation Creates and maintains connectors to external tools from API docs, links, or descriptions.Found in Merge Agent Handler, Jentic Mini
- Policy testing modes Lets teams test rules in a sandbox that logs decisions without blocking before enforcing them.Found in Kastra, Graft AI
- Real-time alerts Sends alerts when unauthorized or policy-violating access attempts happen.Found in Merge Agent Handler, Permit AI Access Control
- Scoped agent keys Gives each agent its own key with limited access that can be revoked immediately.Found in Jentic Mini
- Guardrail rule enforcement Blocks or rewrites risky actions like destructive commands or credential exfiltration based on configurable rules.Found in CtrlAI, Venn.ai, Portia AI
- API catalog search Provides a searchable catalog of API specs to find the right operation without custom wrappers.Found in Jentic Mini
- Self-hosting option Allows deployment on your own infrastructure for control over data and security.Found in Jentic Mini, CtrlAI, Portia AI
- Visual workflow design Offers a visual interface to design and manage how multiple agents work together.Found in Multi-Agent Builder
- Operational mapping Learns how work flows through existing apps and screen-based tools to create stable agent interfaces.Found in Graft AI
- Drift detection and repair Detects when underlying UIs change, stops before side effects, and can repair simple changes automatically.Found in Graft AI
- Identity integration Connects with existing identity management and directory services for permission management.Found in Permit AI Access Control
- Emergency kill switch Provides a way to immediately stop agent actions in case of an incident.Found in CtrlAI, Jentic Mini
How it works, step by step
- Evaluate each agent action against rules and return allow or deny before it runs
- Record every agent action with what was touched and whether it was allowed or blocked
- Route actions that need a person's decision to a human for approval before continuing
- Apply the same controls across multiple agents or frameworks without rebuilding for each
- Connect and configure agent controls without writing code
- Store and inject credentials securely so agents access tools without seeing secrets
- Create and maintain connectors to external tools from API docs, links or descriptions
- Test rules in a sandbox that logs decisions without blocking before enforcing them
- Send alerts when unauthorized or policy-violating access attempts happen
- Give each agent its own key with limited access that can be revoked immediately
- Block or rewrite risky actions like destructive commands or credential exfiltration based on configurable rules
- Provide a searchable catalog of API specs to find the right operation without custom wrappers
- Allow deployment on your own infrastructure for control over data and security
- Offer a visual interface to design and manage how multiple agents work together
- Learn how work flows through existing apps and screen-based tools to create stable agent interfaces
- Detect when underlying UIs change, stop before side effects and repair simple changes automatically
- Connect with existing identity management and directory services for permission management
- Provide a way to immediately stop agent actions in case of an incident
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned operator-approved decision record linked to each executed action 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 Agent action control and audit portal 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 Agent action control and audit portal 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 links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 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 unauthorized or unreviewed agent actions while keeping a complete record of what each agent touched. For platform, security and IT operations teams running AI agents that connect to internal apps, tools and data, convert agent action requests, connector definitions, identity data and policy rules into an operator-approved decision record linked to each executed action. The benefit is a testable hypothesis, measured through blocked unauthorized actions per review hour and unapproved side effects after enforcement; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect agent action requests, connector definitions, identity data and policy rules, then follow this sequence: 1. Evaluate each agent action against rules and return allow or deny before it runs. 2. Record every agent action with what was touched and whether it was allowed or blocked. 3. Route actions that need a person's decision to a human for approval before continuing. Resolve uncertain cases with qualified reviewers, approve operator-approved decision record linked to each executed action, and measure blocked unauthorized actions per review hour and unapproved side effects after enforcement 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 arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One fixed agent framework and connector set; final authorization and incident decisions remain with the security operator. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve least privilege, source attribution, action accuracy and usage permissions. Security operators approve substantive changes and enforcement scope. One fixed agent framework and connector set; final authorization and incident decisions remain with the security operator. 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 fixed agent framework and connector set; final authorization and incident decisions remain with the security operator. Implement one approved input format, a bounded representative case set and the first two task modules: evaluate each agent action against rules and return allow or deny before it runs; record every agent action with what was touched and whether it was allowed or blocked. Support the third module with operator review: route actions that need a person's decision to a human for approval before continuing. 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
Customer-owned agent frameworks, identity providers and permitted internal tools. Cloud or self-hosted deployment, API catalog import/export and alerting 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: Agent and connector registry, Policy and approval console, Action audit and incident view. Use a list of connected agents and tools, a central rule and approval workspace, and a right-hand panel for decision evidence and comments. Let users compare policy versions side by side. Display allowed, denied, pending approval and killed states. Provide a searchable audit view with each decision anchored to the action it governed. Make the task-specific outcome operator-approved decision record linked to each executed action visible beside its evidence, review state and value baseline.
