HighByte’s DataOps Day Stresses the Company as the Horse Before the Cart of AI Empowerment

On October 8, HighByte hosted its final DataOps Day of 2026. The event, held in Boston, geared itself toward highlighting HighByte’s client success, as well as providing the greater manufacturing community with messaging around the importance of—and know-how to--modernize data infrastructure without abandoning all previously existing software investments. The solution: HighByte Intelligence Hub, a no-code industrial Data Operations (DataOps) platform designed to connect, model, contextualize, and govern Operational Technology (OT) information, while providing a strong anchor to enterprise cloud infrastructure.

Industrial data are more plentiful than ever, and manufacturers have quickly learned this is a curse as much as a blessing. Too much data, especially fragmented information from unvalidated or untrustworthy sources slows down decision-making and prevents software infrastructure from scaling with need. HighByte, however, sees data not as a commodity to be controlled, but as a product in and of itself.

The correct data product has an intended customer, a set goal, and a standardized structure complete with quality compliance and delivery system. In this way, customers can create sizable and repeatable data products centered around assets, batches, jobs, quality or alarm events, and processes, organizing them all within a single enterprise system—a unified namespace that solidifies real-time operational data from across numerous points in a manufacturing organization, centralizing it all in a single source of authoritative truth that is dependable and actionable.

Ever since Artificial Intelligence (AI) took centerstage in the manufacturing conversation, a key question has been about how to achieve real value. Research has shown numerous AI-centered projects stall in pilot as they either did not produce the desired results or had no effective way to scale within the organization. This is not the first time a technological innovation has met with resistance during rollout, as similar pilot failures have often been reported with digital thread initiatives, industrial metaverse projects, and other advanced digitization efforts. It is the result of a mentality that chases trends, minimizes infrastructure limitations, and, to use a popular saying, puts the cart before the horse in digital transformation.

HighByte’s perspective and offering are both refreshingly different. Its entire value proposition is built on the horse before the cart mentality. Data are at the core of every digitization effort, so manufacturers first need to invest in a central, contextualized data foundation. However, many newer software platforms position themselves as replacements; for example, having an on-premises legacy Manufacturing Execution System (MES), and upgrading to a new cloud-based model. HighByte’s true value is not just in data contextualization, but in a platform-agnostic approach that lets the customer preserve its existing software investments without the need to overhaul the entire process.

HighByte is part of a fast-growing (and quickly being acquired) market dedicated to providing the data foundation needed for AI and other advanced digital transformation initiatives. HiveMQ, which made an appearance at Tulip’s Ops Calling alongside HighByte (see ABI Insight “Operations Calling 2026: Tulip Impresses Technologically at the Expense of Its People-First Positioning”) is a similar solution, albeit with a stronger focus on acting as a transport layer that connects event-driven data between connected devices, edge environments, and cloud infrastructure using Message Queuing Telemetry Transport (MQTT) compliance standards. While the two companies could compete, they also can work in tandem—with HighByte providing the OT data sourcing, modeling, and contextualization, and HiveMQ then utilizing said structured information to distribute it effectively across the manufacturer’s enterprise via MQTT.

Another company, no longer on the market, that is a clearer competitor to HighByte’s offering is Cognite. Before being acquired by Schneider Electric (see ABI Insight “Schneider Electric’s US$3.1 Billion Cognite Acquisition to Challenge Incumbents’ Industrial Data Analytics and AI Insights Leadership”), Cognite Data Fusion positioned itself with many of the same capabilities, from data integration to contextualization—and in vendor- and software-agnostic ecosystems. It remains to be seen exactly to what extent Schneider Electric’s acquisition will impact the agnosticism of the solution, but it is fair to speculate that Cognite will be more integrated into Schneider’s software offerings.

The race is on to make the most of industrial AI solutions, but few manufacturers will find real success without first properly structuring and contextualizing their data. HighByte is well positioned to take advantage of a real market opportunity, and its inclusion alongside HiveMQ at Tulip’s Ops Calling, along with Schneider Electric’s purchase of Cognite after its acquisition of AVEVA, show that manufacturing software providers understand the importance of putting the horse before the cart.