About agun.ai
Agent University is the certification authority within the DarkNOC ecosystem. It ensures that AI agents are safe, effective, and compliant before they operate on live telecom networks.
What is agun.ai?
agun.ai is the certification layer of the DarkNOC ecosystem. It is where AI agents prove they are safe, effective, and compliant before they are allowed to operate on live telecom infrastructure.
Think of it as an accreditation body. An agent that completes training in agym.ai is not automatically trusted — it must pass a rigorous evaluation that tests not just what it can do, but whether it understands the consequences of its actions and respects its operational boundaries.
The certification process is intentionally conservative. In telecom, an incorrect automated action can affect millions of subscribers. Every agent must demonstrate that it can be trusted with that responsibility.
The DarkNOC Ecosystem
DarkNOC is an autonomous telecom operations platform where AI agents manage, optimize, and protect live network infrastructure. The ecosystem is built on a fundamental principle: no agent operates without proven competency and explicit authorization.
The pipeline from intent to production is deliberate. Every agent must move through four stages: intent declaration, training, certification, and monitored deployment. Each stage has gates that the agent must pass before proceeding.
darknoc.dev
The Platform
The core platform for autonomous network operations. Where human engineers and AI agents collaborate on managing telecom infrastructure.
Visit darknoc.devagym.ai
Training Ground
The training environment where AI agents learn through simulation. Agents practice on digital twins of real network infrastructure before facing certification.
Visit agym.aiagun.ai
Certification
You are here. The certification platform where trained agents are evaluated, certified, and monitored for production readiness.
View DashboardDOIL
Intent Layer
The Declarative Operational Intent Layer. The contract that defines what an agent is allowed to do, its constraints, and its escalation procedures. The foundation of safe autonomy.
Visit darknoc.devThe Pipeline: Intent to Production
Declarative Operational Intent Layer
darknoc.devEvery agent begins as an intent declaration. The DOIL defines what the agent is allowed to do, its operational boundaries, escalation rules, and human oversight requirements. It is a contract between the organization and the autonomous system.
Key Functions
- Intent class definition (e.g., energy-optimization, coverage-analysis)
- Operational constraints and hard limits
- Risk classification and escalation triggers
- Human-in-the-loop requirements and approval workflows
- Audit and compliance requirements
Agent Training Gymnasium
agym.aiThe training environment where agents learn to operate within their DOIL contract. Agents are trained against simulated network environments, historical scenarios, and adversarial edge cases until they demonstrate competency.
Key Functions
- Physics-based network simulation (RF propagation, traffic patterns)
- Historical scenario replay from real network events
- Adversarial testing with injected faults and anomalies
- Progressive difficulty scaling based on agent performance
- Continuous evaluation against the 4-layer scoring framework
Agent University -- Certification
agun.aiThe certification authority. When an agent completes training and achieves minimum threshold scores, it is submitted to the certification pipeline. Here, automated evaluation and human expert review determine whether the agent is fit for production.
Key Functions
- 4-layer automated evaluation (correctness, appropriateness, impact, DOIL compliance)
- Certification levels: Bronze (0.60), Silver (0.70), Gold (0.80), Platinum (0.90)
- Production readiness checklist (guardrails, rollback, staging, audit, human review)
- Expert human review panel for final certification decision
- Continuous monitoring and periodic re-certification
Live Network Deployment
darknoc.devCertified agents are deployed to the live telecom network through the DarkNOC runtime. They operate within their DOIL constraints, under continuous monitoring, with automatic rollback and human escalation capabilities.
Key Functions
- Staged rollout: canary, blue-green, or progressive deployment
- Real-time performance monitoring against certification benchmarks
- Automatic rollback on KPI degradation or constraint violation
- Continuous audit trail with intent-to-action traceability
- Periodic re-certification to maintain deployment authorization
Core Principles
No Agent Touches Production Without Certification
Every agent must pass the full 4-layer evaluation and receive human expert approval before it is authorized for production deployment. There are no shortcuts.
Certification Is Not Permanent
Agents are continuously monitored and periodically re-evaluated. Certification can be suspended or revoked at any time if performance degrades or constraints are violated.
Human Oversight Is Non-Negotiable
Every certification decision involves a human expert review. Even Platinum-certified agents operate under defined escalation paths that include human intervention.
The DOIL Is the Contract
The Declarative Operational Intent Layer defines the boundary of what an agent can do. An agent that operates outside its DOIL, regardless of the outcome, has failed.
Transparency Through Audit Trails
Every decision, every action, every evaluation is logged and traceable. The audit trail connects intent to action to outcome.
Fail Safe, Not Fail Silent
When an agent encounters uncertainty or constraint boundaries, it must escalate, not proceed. Agents are designed to fail safely and visibly.
Why This Matters
Telecom networks are critical infrastructure. They carry emergency calls, enable hospitals, connect businesses, and serve billions of users. An AI agent that makes a bad decision on a live network can cause real harm: dropped emergency calls, service outages, or security breaches.
The certification pipeline exists to ensure that every autonomous action on the network has been validated, reviewed, and approved. It is not about slowing down AI adoption. It is about making AI deployment responsible and trustworthy.
agun.ai is the gate between training and production. If an agent cannot prove it is safe here, it does not reach the network.
Philosophy
Trust is Earned
No agent starts with production access. Trust is earned through demonstrated competence, tested against realistic scenarios, and validated by human experts. There are no shortcuts.
Humans in the Loop
Automation does not mean removing humans. It means giving humans better tools and better information. Every certification decision involves human judgment. Every agent has human oversight.
An Exploration
This is not a finished product. It is an exploration of how we might build trust between humans and AI systems in critical infrastructure. The certification process evolves as we learn.