🏆 HighByte is proud to be recognized as one of the 2026 Best Places to Work in Maine, ranking 6th out of 42 companies in the small employer category! The annual recognition, presented by @BestCompaniesGP, is based on an assessment of company practices, programs, benefits, and employee feedback. 🙏 A big thank you to our team for making HighByte a great place to work. This recognition reflects the people, culture, and shared values that make our company what it is today. #BestPlacestoWork #BestPlacesME #Maine

🔥 It's official: HighByte announces partnership with @databricks, providing the bridge between industrial data and AI-ready analytics for manufacturers like @gerdau. Gerdau, one of the largest steel producers in the Americas, explains the impact of this partnership in production. Using the Intelligence Hub, Gerdau contextualizes OT data closer to its source and streamlines its delivery into the Databricks Data + AI Platform. The result is less custom integration to build and maintain, and faster deployment of new data-driven initiatives. “HighByte has helped us simplify the integration of industrial data into Databricks and significantly reduce the time it takes for operational data to become available to our digital applications.” 💬 Felipe Amorim, Global Tech Architecture Manager at Gerdau Thank you to @PackIot for supporting the deployment and ongoing operation in Brazil. 🗞️ Read the announcement here: bit.ly/4ykai15

Industrial AI doesn’t scale on ambition. It scales on data you can trust. That’s the takeaway from @arc_advisory's Craig Resnick, who joined us at #DataOps Day Boston on October 8. His recap of the day covers: ✅ Why context is the prerequisite for Industrial AI ✅ Why the industry is transitioning from a Unified Namespace to a Data Control Plane as AI agents proliferate ✅ How cloud-native platforms like @awscloud, @Snowflake, and @Siemens Intelligence Center X extend the value of contextualized OT data ✅ Why humans stay accountable in regulated and safety-critical operations Thank you to Craig for the thoughtful summary, and to every speaker and attendee who so candidly shared your perspectives throughout the day. Read the full analysis here: bit.ly/4B5ZAhl

🏗️ HighByte Intelligence Hub 4.5 makes building pipelines faster and easier, so you can spend more time getting value from the software and less time configuring it. In this demo, HighByte CTO Aron Semle shows off a few new features: 🔍 Searchable references, allowing you to find any input by name in seconds 🖼️ Auto-fit view that frames your entire pipeline ⚡ Inline stages on triggers that open their configuration as you drop them 🎯 Path controls on read and write stages to grab exactly the value you need, without extra transform stages Less configuration. Cleaner pipelines. See them for yourself: bit.ly/4jG7wzu

💰 What’s the revenue impact of getting your industrial data strategy right? According to a study conducted by @IDC, manufacturers using #HighByte Intelligence Hub reported $8.75M in additional annual revenue. By integrating with cloud and low-code platforms, organizations accelerated AI innovation and positioned themselves ahead of major competitors. 🔗 See how manufacturers are turning Industrial #DataOps into growth. Download the complete IDC study here: bit.ly/3VGW6S9

🚧 Standing up a new industrial data project can mean a lot of manual steps. Connect to a source; browse the address space; build a model; create an instance; establish a pipeline. That's why we significantly expanded the #MCP configuration tools in HighByte Intelligence Hub to support the use of AI for configuration work.   🎥 In this demo, Aron Semle begins with a completely empty project in the Intelligence Hub and provides a single prompt to an AI agent. From there, the agent uses the new configuration tools to: ✅ Browse the source and locate the injection molding machine data ✅ Create the connections from scratch ✅ Build the data model and instance ✅ Assemble a pipeline that reads the instance and publishes to a topic ✅ Deliver contextualized data to the UNS, in minutes Watch here: bit.ly/4hwxId4

👋 On October 8, manufacturing leaders from @Regeneron, @awscloud, @Snowflake, @Siemens, and more are coming together for #DataOps Day Boston—a 1-day event hosted by HighByte and dedicated to the people rethinking industrial data, from architecture to governance. 🎤 Don't miss Rory Sheehan of Deep Digital Solutions Group kick off the day with a case study on bringing alarm rates at a validated pharmaceutical plant back within globally accepted limits. He'll cover the standards that guided the approach and the AI-driven use cases enabled by a stronger alarm management foundation. Only a few seats are left, so save yours today. All ticket proceeds go to @GirlsWhoCode. 🎟️👇 bit.ly/4hppc10

🗞️ A new edition of the HighByte Resource Round-Up newsletter is here! 💡 Explore new research and analyst perspectives on AI readiness and Industrial #DataOps, plus Intelligence Hub version 4.5 demos and examples from @goustocooking and @Stellantis showing how contextualized industrial data can support analytics and AI at scale. ✅ This edition brings together industry insights, customer examples, and new research to show how manufacturers are improving data quality, demonstrating ROI, and building a stronger foundation for AI. 🔗 lnkd.in/p/eTbF9v5w

🌷 HighByte returns to Operations Calling next week! Join us in Somerville, MA on October 6-7 for @tulipinterfaces' two-day event packed with product announcements and insights from industry experts. The HighByte team will exhibit in the Partner Ecosystem room, ready to talk Industrial DataOps and show you how build the data foundation required for enterprise operations and agentic AI. Staying an extra day? Join us at #DataOps Day Boston on October 8. We have an incredible lineup of speakers with all ticket proceeds going to @GirlsWhoCode. 🎟️ Register here: bit.ly/4dcvEpt

🏋️ What if AI could do the heavy lifting for repetitive #DataOps tasks? This interactive demo shows you how. See for yourself what AI for DataOps looks like in #HighByte Intelligence Hub. Step by step, you'll learn about two capabilities that accelerate how industrial data is modeled and moved: 🤖 The Modeling Agent. Upload context files, prompt your LLM to generate a Model, then accept it or keep iterating. 🤖 The Pipeline AI Agent. Ask AI to explain how an existing Pipeline is configured, then prompt it to change how that Pipeline works—or use the agent to create a new Pipeline—reviewing every proposed modification before you save. 🔗 Explore at your own pace: bit.ly/4ylrTq4