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Velotic has added AI assistant, Model Context Protocol, and agent-development capabilities to the ThingWorx Industrial Intelligence Platform.
Velotic has announced new agentic AI capabilities for its ThingWorx Industrial Intelligence Platform. The additions are intended to help manufacturers connect AI with industrial data, systems, applications, and operational context.
ThingWorx provides the platform foundation for Velotic’s industrial AI strategy, linking operational data and context with industrial applications. The company states that the new capabilities are available with ThingWorx 10.2.
New AI and Agent Capabilities
The release includes three components intended to provide a common foundation for industrial AI assistants and agents:
ThingWorx AI Assistant: An AI assistant capability within the ThingWorx platform.
ThingWorx MCP Server: A Model Context Protocol server that provides a standardized way for AI applications and agents to access ThingWorx data, context, and services.
AI & Agent Services: Development capabilities for creating and extending AI assistants and agents that work with industrial applications and systems.
Together, the additions are designed to give manufacturers a framework for building AI applications that can work with existing industrial data and operational context rather than operating as isolated tools.
Connecting AI with Industrial Context
For industrial AI systems, access to operational context is an important part of turning model outputs into useful actions. Manufacturing environments typically include data distributed across automation systems, historians, enterprise applications, maintenance systems, and other software.
ThingWorx is positioned as the context and application layer connecting these environments with AI assistants and agents. The addition of MCP support is particularly relevant as the protocol is emerging as a standardized interface for connecting AI models and agents with external tools and data sources.
ARC has also been tracking the growing role of industrial data platforms, contextualized data, and MCP in enabling agentic AI. Recent ARC research has emphasized that AI agents require access to trusted operational context if they are to work reliably across manufacturing systems.
Supporting Industrial AI Development
Velotic is positioning the new capabilities as part of its broader Industrial Intelligence strategy, with ThingWorx serving as the platform layer connecting industrial data, applications, and AI.
The update reflects a broader shift in industrial software from standalone AI assistants toward agentic architectures that can access operational data, interact with applications, and participate in multi-step workflows. Open interfaces such as MCP are becoming increasingly relevant as manufacturers look to connect AI agents with existing industrial systems while avoiding highly isolated implementations.
Related ARC Insights
ARC has been examining the relationship among industrial data platforms, operational context, MCP, and agentic AI as manufacturers move from AI pilots toward broader deployments.
Scaling Manufacturing with Industrial DataOps and Agentic AI
Industrial AI SPARC: Software Defined Manufacturing in the Era of Agentic AI
Taming the Agentic Swamp: Anchoring Autonomy with Industrial-Grade Data Fabric
The ThingWorx additions illustrate how industrial software platforms are evolving to provide AI systems with structured access to operational data, applications, and context as agentic AI becomes more widely applied in manufacturing.