SORBA.ai and Coreflux partner on industrial AI data pipelines

SORBA.ai and Coreflux announced a technical strategic partnership on September 10, 2026, to connect industrial MQTT data infrastructure with no-code AI tools. The companies say the effort is meant to help manufacturers move from machine data to prediction, optimization, and operational action without replacing existing systems.

Why it matters: - The partnership targets a core industrial AI bottleneck: getting machine, sensor, and control-system data into usable AI models. - The combined stack is intended to give manufacturers and critical infrastructure operators a faster path from connectivity to predictive analytics and closed-loop control. - The collaboration is also aimed at edge-first and on-premise deployments, which can help keep sensitive production data closer to operations.

What happened: - SORBA.ai announced a technical strategic partnership with Coreflux on September 10, 2026. - SORBA.ai provides no-code industrial AI and machine learning software. - Coreflux provides MQTT-based industrial IoT infrastructure, industrial connectivity, and edge computing. - The companies plan to combine Coreflux’s data pipelines with SORBA.ai’s AI platform. - The goal is to create a streamlined route from operational data to AI-driven action.

The details: - Coreflux’s platform supports MQTT, Modbus, OPC UA, Siemens S7, and Allen-Bradley. - Coreflux can move data between industrial equipment, databases, APIs, cloud platforms, and other MQTT environments. - Coreflux can be deployed across edge, on-premise, containerized, and cloud architectures. - SORBA.ai lets engineers, operators, systems integrators, and subject-matter experts build and deploy analytics without dedicated data science teams. - SORBA.ai capabilities include anomaly detection, predictive maintenance, regression and virtual sensors, forecasting, digital twins, Remaining Useful Life and Time to Failure models, process optimization, computer vision, and closed-loop control. - The companies said the architecture could look like: PLC, sensor, or machine data flowing through Coreflux into a unified data layer, then into SORBA.ai models, and then into prediction, optimization, and operational action. - Coreflux’s MQTT architecture is designed to support Unified Namespace strategies by decoupling operational data from individual applications. - SORBA.ai can use contextualized operational data to build models for equipment health, process behavior, quality, energy consumption, and production performance. - Coreflux’s human-readable Language of Things can handle automation rules, data models, transformations, and routing logic near the source of industrial data. - SORBA.ai also supports on-premise and edge deployment. - The companies said that approach can help organizations keep control of operational data while deploying AI across plants, production lines, and distributed assets. - The partnership is also intended to work alongside existing PLC, SCADA, DCS, historian, MES, database, and enterprise environments. - Coreflux provides connectivity and data movement across legacy and modern industrial systems. - SORBA.ai provides the intelligence layer for identifying patterns, predicting future conditions, simulating operating scenarios, and optimizing processes. - The companies expect the partnership to support predictive maintenance, process anomaly detection, virtual sensors, Remaining Useful Life and Time to Failure prediction, quality prediction, energy and utility optimization, production forecasting, digital twins, process optimization, industrial computer vision, Unified Namespace architectures, edge AI and analytics, and closed-loop optimization and control.

Between the lines: - The partnership reflects a broader push in industrial software toward open architectures instead of rip-and-replace automation projects. - The joint message centers on interoperability, which can reduce the need for another isolated data silo. - Edge and on-premise support suggests the companies are positioning for factories and infrastructure sites that have strict latency, security, or data-governance requirements. - Bryan Thyken, chief revenue officer of SORBA.ai, said industrial AI is only as effective as the operational data feeding it. - Hugo Vaz, CEO and co-founder of Coreflux, said the combination shows what an open industrial architecture should look like.

What's next: - The companies plan technical integrations, reference architectures, joint demonstrations, customer deployments, systems integrator enablement, and industrial AI use cases. - SORBA.ai and Coreflux also plan to show how MQTT and Unified Namespace architectures can support industrial AI at scale. - The partnership is meant to move customers from connectivity, to contextualization, to intelligence, to action. - Coreflux says its hub combines MQTT broker technology, industrial protocol connectivity, data routing, edge computing, and the Language of Things. - Coreflux says it supports deployment on Windows, Linux, Docker, edge hardware, and cloud environments. - SORBA.ai says more information is available at the company’s website. - Coreflux says more information is available at the company’s website.

The bottom line: - The partnership is designed to make industrial AI easier to deploy by pairing real-time industrial data plumbing with no-code machine learning tools.