Industrial software company announces general availability of HighByte Intelligence Hub version 4.2, enabling Agentic and AI-assisted DataOps at the edge
HighByte, an industrial software company, announced the release of HighByte Intelligence Hub version 4.2 with an embedded Industrial Model Context Protocol (MCP) Server that powers Agentic AI and new LLM-assisted data contextualization via native connections to Amazon Bedrock, Azure OpenAI, Google Gemini, OpenAI, and local LLMs.
HighByte Intelligence Hub provides the first Industrial MCP Server to expose data pipelines as “tools” to AI agents, including descriptions and parameters. With the Intelligence Hub, AI agents can securely access all connected industrial systems and make real time or historical data requests on them.
“The Industrial MCP Server for HighByte Intelligence Hub enables us to rapidly prototype and experiment with Agentic AI on our shop floor,” said Andrey Gorbokonenko, Senior IT Business Intelligence Developer at Idahoan Foods. “We are leveraging HighByte’s broad connectivity to integrate data from multiple sources and curate contextualized datasets for AI Agents focused on quality process control improvement. We’re particularly excited about developing agents that enable Plant Operators to interact with data in a more natural, conversational manner. HighByte provides the data infrastructure we need to address current use cases and support future digital transformation initiatives.”
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According to ARC Advisory Group, one of the key challenges in utilizing Industrial AI technology has been its ability to understand the complexity of industrial environments. While industrial data is abundant and valuable, its fragmented nature has made seamless integration with AI models a particularly difficult task.
“HighByte Intelligence Hub solves this challenge,” said John Harrington, Chief Product Officer at HighByte. “The Intelligence Hub is an Industrial DataOps solution that contextualizes and standardizes industrial data from diverse sources for diverse targets. Agentic AI clients on the factory floor are a natural extension of this approach. We’re enabling DataOps to feed AI, and AI to assist and scale DataOps.”
The latest release also introduces Git integration and OpenTelemetry (OTel) support to scale and manage deployments using DevOps tooling for version control and observability. Users will also have access to new Databricks and TimescaleDB connectors and enhanced connectivity with Apache Kafka and Amazon S3 for cloud-to-edge use cases. Furthermore, the Oracle Database connection has been enhanced to support Change Data Capture (CDC), the Snowflake SQL connection now supports write operations, and the AVEVA PI System connection supports enhanced PI point metadata reads. These capabilities optimize bi-directional connectivity for the many disparate data services found in the cloud, data center, and factory floor.
Source: Businesswire