XMPro Named as Sample Vendor for Agentic AI in Gartner® Emerging Tech Impact Radar

XMPro Named as Sample Vendor for Agentic AI in Gartner® Emerging Tech Impact Radar: Disruptive Technologies in the Far Horizon

DALLAS, TX, UNITED STATES, June 23, 2025 /EINPresswire.com/ -- XMPro, a leading provider of industrial AI and intelligent business operations solutions, today announced it has been named as a Sample Vendor for Agentic AI in the Gartner^® report Emerging Tech Impact Radar: Disruptive Technologies in the Far Horizon, published on June 6, 2025.*

We believe this recognition reflects the company’s ongoing innovation in applying advanced AI to complex industrial environments. The report states, “High-impact emerging technologies in the 6-to-8-year horizon represent far future disruptors to tech offerings and markets. Product leaders must plan for the disruption these far-out emerging technologies represent, plan for future innovations, and invest in first-mover advantage.”

The report defines Agentic AI as "various architectures, techniques, and frameworks for creating single-agent or collaborative multiagent systems capable of unsupervised task execution." (1)

According to the report, "Advancements in agentic AI, causal AI and active inference will enable highly autonomous systems and actuation in dynamic and complex digital and physical environments." (1)

"We believe XMPro’s platform is uniquely aligned with the characteristics Gartner identifies for Agentic AI, and purpose-built for industrial decision intelligence in mission-critical, heavy asset environments," said Pieter van Schalkwyk, CEO of XMPro. "While much of the market is focused on applying agentic AI to back-office and business processes, XMPro’s architecture enables cognitive engineering agents to support real-time operational decisions on the factory floor, in the mine, across the grid, and within complex industrial systems, where trust, traceability, and performance are essential."

“The XMPro architecture was designed from the outset to reflect core principles of cognitive intelligence required for industrial operations,” said Gavin Green, VP of Strategic Solutions, XMPro. “Independent external research, such as the recent paper Advances and Challenges in Foundation Agents, authored by researchers from Meta, Google DeepMind, Stanford, Microsoft Research, CIFAR, Yale, and others, has strongly validated these architectural principles — confirming that modular memory systems, collaborative agent teams, and causal reasoning are critical for safely applying Agentic AI in mission-critical industrial environments.”

(1) Source: Gartner, Emerging Tech Impact Radar: Disruptive Technologies in the Far Horizon, Danielle Casey, Tuong Nguyen, 6 June 2025.
GARTNER is a registered trademark and service mark of Gartner, Inc. and its affiliates and is used herein with permission. All rights reserved.
Gartner Disclaimer: Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

XMPro’s Approach to Industrial Agentic AI
XMPro’s Multi-Agent Generative Systems (MAGS) platform delivers Agentic AI purpose-built for industrial and mission-critical environments. MAGS cognitive agents optimize real-time decisions against engineering-grounded objectives, driving outcomes for physical assets and safety. Agents operate within strict safety and governance boundaries, with clear separation of decision logic and execution control, and provide full transparency through auditable reasoning and explainable outputs.

Graduated Autonomy Framework
Organizations can configure agent autonomy based on operational risk, compliance, and trust requirements. Agents operate in supervised, semi-autonomous, or fully autonomous modes, enabling controlled progression toward higher levels of automation.

Truth-Grounded Composite AI Architecture
Agents ground decisions in verified industrial data and engineering principles, combining first-principles physics models, symbolic AI for rule-based safety constraints, causal AI for root-cause reasoning, and real-time operational and engineering data.

Flexible and Secure Deployment
XMPro supports flexible deployment across on-premise, edge-native, private cloud, public cloud (Microsoft Azure, AWS, Google Cloud Platform), and hybrid architectures, giving organizations full control over data locality, latency, and governance. The platform is model-agnostic and supports leading AI models from OpenAI, Anthropic, Google DeepMind, Meta, NVIDIA, Microsoft Azure, and private or fine-tuned models.

Industrial Communication Standards and Advanced AI Integration
XMPro natively supports industrial communication standards including MQTT, OPC UA, REST APIs, AMQP, and DDS, ensuring seamless integration with industrial control systems and mission-critical infrastructure. Agents can also access protocols such as Model Context Protocol (MCP), and Agent-to-Agent (A2A) protocols.

Accelerating Industrial Adoption Through Strategic Partnerships
XMPro recently demonstrated its Multi-Agent Generative Systems (MAGS) at Hannover Messe 2025 in collaboration with Dell Technologies and its ecosystem partners. XMPro is also included in the Dell Validated Design for Manufacturing Edge program, providing pre-tested, industrial-grade solutions that can be deployed with confidence at the edge. As part of the Dell AI Factory initiative, which combines enterprise AI infrastructure from Dell with accelerators from partners such as NVIDIA, XMPro provides industrial enterprises with a production-ready path to deploying scalable agentic AI on trusted infrastructure.

XMPro’s proven Decision Intelligence solutions form the foundation for its advanced Agentic AI capabilities. These solutions have already delivered measurable value for Global 2000 companies, with documented results including millions in annual savings, double-digit reductions in downtime and field service costs, and successful large-scale deployments across mining, oil & gas, and manufacturing sectors.
Organizations interested in exploring XMPro’s agentic AI solutions can learn more at www.xmpro.com.

About XMPro
XMPro is a leading industrial AI company helping enterprises achieve measurable business outcomes through intelligent operations. Its Multi-Agent Generative Systems (MAGS) platform combines industrial digital twins with trusted agentic AI to optimize operations, improve asset performance, and support complex decision-making. XMPro solutions are trusted by Fortune 500 and Global 2000 companies across mining, energy, chemicals, manufacturing, and utilities sectors, including some of the world’s largest resource producers and industrial operators. The company is also an active member of the Digital Twin Consortium and a participant in the Dell Validated Design for Manufacturing Edge program.

Wouter Beneke - Marketing Lead
XMPro
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Introductory Demo: XMPro's Collaborative AI Agent Teams For Industrial Operations