STAGE 01 FOUNDATION
Decision Support
The foundation that transforms alert overload into orchestrated action.
Explore Decision SupportDECISION AUTOMATION · AUTONOMOUS
Trusted, reliable, explainable autonomous operations.
Bridge the gap between needing AI agents and trusting them with control. XMPro’s Multi-Agent Generative Systems deliver the transparency, explainability, and safety that industrial operations demand.
The third stage of XMPro’s decision continuum.
Decision Automation builds on Decision Support and Decision Augmentation. Trusted autonomy emerges from a foundation of clean data, explainable recommendations, and human-in-the-loop confidence.
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- STAGE 02 ASSISTED
Decision Augmentation
From knowing what is happening to knowing what to do, with AI-augmented guidance.
Explore Decision Augmentation - STAGE 03 CURRENT
Decision Automation
Trusted, reliable, and explainable autonomous operations.
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The barrier to autonomy isn’t the AI. It’s what sits underneath it.
Most teams will not hand control to systems they cannot inspect, constrain, or override. Governance is what closes the gap.
Why traditional autonomous AI approaches fall short.
Most "AI agents" today are sophisticated chatbots. Useful at the desk, dangerous on the line.
F1 RISK
LLM-as-Brain Dependency
Systems that are LLM wrappers with no true autonomy or independent reasoning. The model is the brain, the safety boundary, and the audit trail. None of those should be the same thing.
F2 RISK
Black-Box Explainability
Operators are asked to trust outputs they cannot inspect. No clear rationale, no decision trail, no way to audit what happened or why.
F3 RISK
Reliability and Safety Gaps
Single points of failure, no hard safety boundaries, performance varying with model parameters and provider updates.
F4 RISK
Scalability and Maintenance
Prompt drift changes behaviour unpredictably. Model dependency breaks systems with provider updates. No durable platform layer.
F5 RISK
Integration Disconnect
Fragile API connections. No industrial protocol support (OPC UA, MQTT, DDS). Security limited to basic API keys.
F6 RISK
No Learning or Adaptation
Stateless operations with no memory, no learning framework, no knowledge transfer between agents or shifts.
F7 RISK
Pseudo Multi-Agent Systems
Most "multi-agent" architectures are sequential scripts, not autonomous teams. Hard-coded glue, not a governed platform.
F8 RISK
No Decision Governance
No clear audit trail, rationale tracking, or feedback loop between agents and humans. Compliance and safety review become impossible.
Trusted autonomous agents that observe, reason, and act inside rules of engagement.
Decision Automation lets agents continuously observe, reason, and act across complex industrial systems while maintaining transparency, explainability, and human oversight.
A platform-grade architecture for autonomous operations.
XMPro Multi-Agent Generative Systems address each failure mode directly: continuous memory, deterministic decision logic, consensus coordination, separation of control, edge deployment, and full lifecycle management.
M1 MEMORY
Advanced Memory Architecture
Agents maintain continuous memory through ORPA cycles (Observe-Reflect-Plan-Act). Significance scoring and memory consolidation let agents build institutional knowledge and share insights across the team.
M2 DETERMINISTIC
90% Business Logic, 10% LLM
Mathematical optimization drives decisions, not probabilistic text generation. LLMs serve as text-processing utilities. Deterministic systems handle the critical choices.
M3 CONSENSUS
Consensus-Driven Coordination
Formal consensus protocols with a communication broker. Different algorithms based on decision criticality, escalating to higher thresholds for safety-critical choices.
M4 CONTROL
Separation of Control
Strict separation between cognitive decision-making and physical execution. MAGS action plans flow to DataStream Action Agents for controlled, safety-validated implementation.
M5 EDGE
Edge-to-Cloud Autonomy
With AMD Ryzen AI acceleration, MAGS can deploy at the industrial edge. No cloud round trips for critical decisions. Sensitive data stays in the facility. Autonomy continues during connectivity loss.
M6 LIFECYCLE
APEX Lifecycle Management
The Agent Control Tower provides real-time team performance, global command view, intelligent alerting, resource management, and an MQTT-based communication hub for active agents.
MAGS and APEX, together.
Autonomous agent teams and the orchestration platform that governs them. Cognition and control, designed as one architecture.
MAGS OPS AGENTS
Multi-Agent Generative Systems are collaborative agent teams for industrial operations. Specialized agents — reliability, process, planning, safety — that observe, reflect, plan, and act on shared operational context.
Autonomous goal pursuit inside rules of engagement
Hybrid generative and deterministic decision-making
Real-time industrial optimization across assets
Bounded autonomy with deontic governance
APEX AGENTOPS
The Agentic Platform Experience is your control room for industrial AI agents. Real-time monitoring, global command, intelligent alerting, resource management, and an MQTT-based communication hub.
Real-time team performance across operations
Unified visibility across intercontinental sites
Priority alerting with automated escalation
Audit trail and rationale tracking
Bring trusted autonomy into your operations.
Talk through where governed autonomous agents fit your environment, or explore the broader XMPro platform.
