Operators maintain control while autonomous agents execute at scale.
The gap between traditional automation and modern operational requirements demands a new approach.
Seven integrated layers that enable mission-critical autonomous operations.
Translates high-level objectives into executable multi-step plans. Decomposes complex missions into coordinated agent tasks with dependency management.
Operators define intent, not implementation. The planner handles tactical decomposition while maintaining strategic alignment.
Dynamic replanning on failure. If an agent hits an obstacle, the planner adapts without operator intervention.
Real-time coordination of multiple AI agents. Manages task assignment, resource allocation, inter-agent communication, and execution timing.
Single agents are limited. Coordinated swarms multiply capability. The orchestrator is the command layer that makes multi-agent operations coherent.
1Hz heartbeat monitoring with automatic failover. Agents that go dark are detected and replaced within seconds.
Specialized AI agents for different mission profiles: offensive operations, defensive monitoring, research analysis, forensics, and incident response.
Different tasks require different capabilities. Purpose-built agents outperform generalists on specialized missions.
LLM-agnostic architecture. Deploy Claude, GPT, or local models based on classification requirements. No vendor lock-in.
Standardized interfaces to operational tools: osquery, YARA, Sigma, Volatility, tshark, Sysmon, and custom integrations.
Agents don't just thinkβthey act. Tool adapters bridge AI reasoning to real-world execution with validated outputs.
Structured output validation. Tool results are parsed, verified, and formatted before agent consumption. No hallucinated tool outputs.
Real-time reasoning transparency. Operators can query any agent mid-execution: "Why did you choose this approach?" and get immediate explanations.
Trust requires understanding. In defense contexts, operators must know why an agent took an action, not just what it did.
Interactive steering. Don't just observeβintervene. Adjust agent behavior mid-mission without stopping execution.
Multi-level approval system: Allow once, Allow for session, Allow always, Deny. Silent-command watchdog detects unauthorized execution attempts.
Autonomous systems must have hard limits. The safety layer ensures agents operate within defined boundaries with human approval gates.
Policy enforcement with cryptographic verification. Approval decisions are logged, signed, and auditable.
Complete audit trail of every decision, action, and outcome. Traceable chain from operator intent through agent execution to mission result.
Accountability requires records. Post-mission analysis, compliance audits, and continuous improvement all depend on decision provenance.
Mission replay capability. Review any operation step-by-step with full context reconstruction.
Operators don't just watch. They understand, query, and steer.
Selected lateral movement detection playbook based on:
Confidence: 94% | Alternative considered: Brute force (rejected, no password spray pattern)
Ask agents why they chose a specific approach. Get structured reasoning traces, not vague summaries.
Adjust agent focus without stopping execution. Add constraints, shift priorities, or redirect attention.
See uncertainty levels for every decision. Agents that aren't sure say soβand explain why.
Autonomy without accountability is liability. Every action is gated, logged, and reversible.
Four-tier permission system for sensitive operations:
Monitors for unauthorized execution attempts. If an agent tries to bypass approval gates or execute unregistered commands, the watchdog intervenes immediately.
Define operational boundaries before mission start. Policies specify allowed tools, forbidden actions, escalation thresholds, and automatic halt conditions.
policy: no_destructive_ops
escalate_on: privilege_change
halt_if: network_exfil > 10MB
Every agent action is reversible. If a mission goes sideways, operators can roll back to any checkpoint with full state restoration.
End-to-end visibility from operator intent to mission completion.
Real demonstrations of Automedon coordinating autonomous agents for mission-critical operations.
Coordinated multi-agent reconnaissance and exploitation. Watch four agents work in parallel while maintaining operator oversight.
SENTINEL swarm conducting incident response. Threat hunting, forensics, and containment with full PICERL workflow automation.
Ensure the United States leads the cyber domain in the age of AI.
Automedon Technologies builds human-guided autonomous systems for defense and critical infrastructure. We believe the future of cyber operations requires AI that can act, not just advise β with humans firmly in control.
Connect with defense professionals deploying AI-powered operations.
Real-time discussions, mission debriefs, and technical support.
Coming SoonDeep-dive technical discussions and playbook sharing.
Coming SoonCertification for Automedon operators and integrators.
Coming SoonCurrently in limited release for defense and enterprise partners.