This is a submission for the Auth0 for AI Agents Challenge
💡 What I Built
Clarity Flow is a secure, AI-driven business management platform that helps teams organize and manage operations through natural language interactions.
It combines conversational AI with enterprise-grade security, ensuring every AI action is authenticated, authorized, and auditable.
The platform features a React + Vite frontend for interactive dashboards and a Fastify backend API integrated with Google Gemini AI for contextual reasoning and command execution.
🔧 Key Features
- Dashboard: Real-time view of company metrics and activity
- Appointments Management: AI-assisted meeting scheduling and coordination
- Employee Management: Manage users, roles, and departments
- Task Tracking: Assign and monitor tasks through natural language
- Sales Monitoring: Track performance, deals, and pipelines
- AI Chat Interface: Conversational AI that performs CRUD operations securely
- Auth0-Powered Security: Authentication, role-based authorization, and department-aware data access
Example queries the AI can handle:
“Schedule a meeting with John tomorrow at 2 PM”
“Show all open sales deals in my department”
“List pending tasks for the marketing team”
All actions are automatically scoped by the user’s role and department.
🎥 Demo Video
🚀 Live Demo & Repositories
Frontend: https://github.com/wesleybertipaglia/clarity-flow-app
API: https://github.com/wesleybertipaglia/clarity-flow-api
Live App: https://clarity-flow-app.vercel.app
To try it out:
- Visit the live demo
- Authenticate via Auth0
- Use the AI chat to manage data with prompts like:
- “Create a new task for the sales department”
- “List all upcoming HR meetings”
- “Show me marketing performance for this month”
🔐 How I Used Auth0 for AI Agents
Auth0 for AI Agents is the foundation of Clarity Flow’s security model, ensuring that both users and AI agents operate strictly within their allowed permissions.
🧾 User Authentication
- Auth0 Login Flow: Users authenticate through Auth0 and receive JWT access tokens.
- Secure User Prompts: Every AI interaction is tied to an authenticated identity, preventing anonymous or unauthorized requests.
- Token Validation: The backend validates tokens on every API and AI request.
🧠 Authorization Model – Roles & Departments
Clarity Flow enforces a hierarchical authorization system that governs what users (and the AI acting on their behalf) can access or modify:
👑 Owner
- Full administrative privileges across the platform.
- Can perform CRUD operations on all resources (employees, tasks, appointments, sales, etc.).
- Has visibility across all departments.
🧩 Managers
- Have CRUD permissions for resources within their assigned department.
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Example:
- HR managers can create, update, or delete employee records.
- Sales managers can manage sales data and deals.
- Marketing managers can control campaigns and tasks.
Cannot access or modify data belonging to other departments.
👷 Employees
- Have read-only access limited to their own department’s data.
- Can view tasks, appointments, and metrics relevant to their work but cannot create, update, or delete records.
This structure ensures that every action — including AI-triggered ones — respects both role-based and department-based boundaries.
🤖 AI Agent Authorization & Delegation
- Delegated Permissions: The AI agent inherits the authenticated user’s permissions, so every operation it performs is authorized as if the user executed it manually.
- Token Vault Integration: Auth0’s Token Vault secures external API access (like Gemini AI) without exposing secrets.
- Action-Level Enforcement: When the AI executes a command (e.g., “create a task”), the backend checks the user’s role and department before allowing the operation.
- Context-Aware Responses: The AI filters responses dynamically, showing only the data the current user is permitted to view.
⚙️ Implementation Details
- Backend (Fastify): Validates Auth0 JWTs and enforces role + department access rules before invoking AI tools.
- Frontend (React): Uses the Auth0 SDK for authentication and token lifecycle management.
- AI Flow (LangChain): Each AI tool in the pipeline performs authorization checks before CRUD actions are executed.
This combination ensures that no AI-generated command can bypass organizational policies.
🧩 Lessons Learned
Building Clarity Flow reinforced the importance of merging secure identity management with AI flexibility.
Key Challenges
- Mapping Roles to AI Behavior: Translating human access rules into enforceable AI tool permissions.
- Maintaining Conversational UX: Keeping the AI experience fluid while enforcing strict permission boundaries.
- Managing Tokens Across Layers: Handling user and agent tokens securely across frontend, backend, and AI contexts.
Technical Insights
- Auth0 for AI Agents Simplified Secure AI Integration: Token Vault and delegated permissions made the design much safer.
- Role + Department Hierarchy: Combining both dimensions gives organizations precise, intuitive control.
- Permission-Aware AI is Essential: Prevents data leakage and builds trust in AI-powered workflows.
Advice for Developers
- Design for Authorization Early: Treat access control as a first-class design concern.
- Test Role and Department Scenarios: Ensure your AI can’t “jump boundaries.”
- Balance UX and Security: Good AI design should feel natural but stay compliant.
- Leverage Auth0’s Tools: They eliminate boilerplate and reduce security risks.
✅ Takeaway
Clarity Flow demonstrates how AI agents can operate securely within business systems using Auth0 for AI Agents.
By enforcing role-based and department-based authorization, every AI action is accountable, permission-bound, and auditable — enabling secure automation for real-world organizations.
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