Published October 6, 2026

New Partnership Between AI & Automation Companies


 SORBA.ai, a no-code industrial AI software provider, announced a strategic channel partnership with E Tech Group, a North American industrial automation and systems integration firm. The partnership is focused on deploying predictive maintenance, advanced process control (APC) and closed-loop AI models that integrate directly into industrial control environments to deliver measurable, real-time operational outcomes.

The collaboration brings together SORBA.ai’s modular industrial AI platform with E Tech Group’s deep expertise in controls engineering, OT/IT integration and lifecycle services. Together, the companies will help industrial organizations transition from isolated analytics and pilot projects to production-grade AI systems that actively influence operations, improve asset reliability, and optimize process performance.

Industrial operators increasingly recognize that AI value is only realized when models are engineered into day-to-day operations. Through this partnership, E Tech Group will deploy SORBA.ai solutions as part of integrated automation and digital transformation initiatives, ensuring AI models are aligned with control strategies, operational constraints, and safety requirements.

By embedding AI directly into operational workflows, customers can move beyond alerts and dashboards to prescriptive and autonomous decision-making, enabling faster response times, improved consistency, and sustained performance gains.

As part of the partnership, E Tech Group will deploy SORBA.ai’s modular industrial AI platform, including:

DataBridge – Securely connecting PLCs, DCS, SCADA, historians, MES, and enterprise systems to establish a governed, real-time data foundation

  • Detect & Predict (Predictive Maintenance Suite) – AI models for anomaly detection, asset health monitoring, and early fault detection
  • Simulate & Control (Advanced Process Control Suite) – Digital twins, multivariable optimization, and AI-driven APC strategies
  • VisionAI Module – Computer vision for quality inspection, defect detection, and visual process monitoring

These capabilities allow engineering and operations teams to rapidly design, deploy, and scale AI models using their own domain knowledge, without reliance on scarce data science resources, all while supporting on-prem and hybrid architectures common in regulated and mission-critical environments.

From Predictive Maintenance to Closed-Loop Optimization

SORBA.ai’s platform is purpose-built to bridge the gap between analytics and action. When deployed by E Tech Group, AI models can be integrated directly into control strategies to support closed-loop execution, enabling use cases such as:

  • Predictive maintenance models that prevent unplanned downtime and extend asset life
  • AI-driven setpoint optimization that adapts to changing process conditions
  • Continuous quality optimization to reduce scrap, rework, and off-spec production
  • Energy, throughput and yield optimization driven by real-time process intelligence

With more than 30 years of experience and hundreds of engineers supporting complex industrial systems, E Tech Group brings the operational rigor required to deploy AI safely and reliably. The partnership supports scalable AI adoption while preserving cybersecurity, data sovereignty, deterministic control behavior and system uptime.

E Tech Group’s experience deploying modern SCADA, DCS and IIoT platforms, allows SORBA.ai models to be operationalized efficiently within existing architectures, without disrupting proven automation strategies or operator workflows.

“AI has to work within the realities of industrial operations,” said Akshatha Shetty, Director of AI Solutions at E Tech Group. “This partnership with SORBA.ai allows us to deploy predictive maintenance and advanced control solutions that are tightly integrated with automation systems, engineered for reliability, and aligned with how our customers actually run their plants. Together, we’re helping clients move from AI experimentation to sustained operational impact.”

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