Platform Access

Current access is provided via a recorded live pilot demonstration while cloud infrastructure is being provisioned. This recorded pilot demonstration is the primary access path used to evaluate platform functionality during early-stage deployment. 

How the Demo Is Run (Pilot Environment)

The demonstration is executed using a controlled local pilot environment.

Core steps include:

1. Operator starts the agent controller
   
   

2. System prompts for human approval
   
   

3. Approved action activates the agent endpoint
   
   

4. Endpoint enters listening/operational state and logs activity

LEBNI Platform Overview

Secure, Human-in-the-Loop AI Infrastructure for Public Safety

The LEBNI Platform is a secure AI infrastructure system designed to support communication, coordination, and decision-support workflows for law enforcement and public safety agencies. The platform is built around human-in-the-loop AI agents, where AI systems assist with information processing and routing, but all operational actions require explicit human review and authorization.

This design prioritizes accountability, transparency, and alignment with public-sector governance and compliance requirements.

AI Agent Control Interface

(Screenshot: AI Agent Control Dashboard)

The LEBNI platform provides an operator-facing control interface used to start, manage, and monitor AI agent services during pilot operation.

From this interface, authorized users can:

• Start or stop agent services
  
  

• Monitor agent operational status
  
  

• Initiate test workflows
  
  

• Access supporting system utilities
  
  

The control dashboard enforces controlled execution, ensuring agents operate only within approved workflows and under operator supervision. This interface forms the primary point of human oversight during deployment and testing.

Human-in-the-Loop Review & Approval Flow

(Screenshot: Human-in-the-Loop Review and Approval Flow)

Before initiating sensitive actions—such as starting an agent-accessible REST endpoint—the system pauses and requires explicit human approval.

AI agents may recommend actions or prepare operational steps, but no action executes without human confirmation. Approval or rejection decisions are logged, preserving operator accountability and preventing autonomous execution.

This approval gate ensures:

• Human authority over all operational actions
  
  

• Clear separation between AI assistance and human decision-making
  
  

• Oversight during pilot and early deployments
  
  

Agent Endpoint Listening / Operational State

(Screenshot: Agent Endpoint Listening / Operational State)

Once approved by a human operator, the AI agent successfully enters an operational listening state on a controlled endpoint (shown here in a localhost pilot environment).

The system visibly confirms:

• Endpoint activation
  
  

• Listening state
  
  

• Port and route details
  
  

Endpoints are activated only through operator action and are designed for auditable, secure pilot operation.

Note: Localhost endpoints are shown for demonstration purposes. Production deployments operate behind authenticated gateways and are not publicly exposed.

Development Status

LEBNI is currently in the early-stage development and pilot validation phase. Active development focuses on:

• AI agent orchestration
  
  

• Human-in-the-loop workflow enforcement
  
  

• Secure cloud deployment patterns
  
  

• Auditability and operational accountability
  
  

The platform is being built with an emphasis on responsible AI, public-sector alignment, and operational safety.

LEBNI is seeking cloud infrastructure support to accelerate development, testing, and pilot deployment of this platform.