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CHARLOTTESVILLE, VA  |  April 21, 2026 — This week, TwinThread—a global leader in Industrial AI—was named a Front Runner in LNS Research’s inaugural 2026 Industrial AI Platforms Solution Selection Matrix (SSM). TwinThread’s positioning in the Front Runners upper right and most favored quadrant recognizes the company’s comprehensive product innovation, scalable architecture, and distinct and pragmatic approach to deploying agentic AI for manufacturing operations.


LNS Research, a premier research and advisory firm for the industrial sector, conducted this evaluation using its rigorous "3P Evaluation Model" to assess candidates’ ability to serve the rapidly evolving industrial AI market. The evaluation scores suppliers across three critical dimensions:

Product: Compares candidate capabilities against the LNS Research Industrial AI Functionalities Stack, consisting of key characteristics for industrial advanced analytics, data platforms, and dataOps functionalities.

● Potential: Measures capacity for long-term growth and viability, factoring in scale, market positioning, financial resources, and management strategy.

Presence: Assesses global market prominence, proven customer success, and the vendor's capability to serve diverse industries and customer sizes.

As a Front Runner, TwinThread was commended for invoking an execution-focused approach that prioritizes tangible operational value over generic AI hype, empowering business users, process engineers, and subject matter experts to collaborate and solve high-impact problems at scale.
TwinThread’s strong positioning in the matrix is driven by its robust and purpose-built industrial AI capabilities. The company provides a comprehensive edge-to-cloud platform, with prebuilt ISA-88 batch system integration and Model Factories for rapid and repeatable deployment. It maintains a core suite of ready-to-deploy applications for delivering advanced predictive and prescriptive analytics, including the ability to make closed-loop setpoint adjustments.

Furthermore, TwinThread stood out in the selection for its distinct, disciplined approach to agentic AI. Rather than rushing generic AI offerings to market, the company employs a three-pronged strategy that combines ML-driven analytics, autonomous orchestrating agents, and an intuitive user interface.

Beyond its core technology, TwinThread is recognized for its exceptional flexibility and scalability. The platform is engineered to accommodate diverse manufacturing environments and varying levels of digital maturity, operating seamlessly at scale across multiple sites, all without requiring heavy customization. This helps users secure quick wins and progressively expand into full-stack integrations. Additionally, TwinThread's strategic presence within the global industrial ecosystemfurther underscores its industry expertise and ability to deliver widespread value.

“Being recognized as a Front Runner by LNS Research validates our core mission to amplify human expertise through purpose-built Industrial AI,” says Erik Udstuen, co-founder and CEO at TwinThread. “In a crowded market, our execution-focused strategy stands out because we don't just deliver data models, but instead provide actionable, closed-loop solutions. This positioning reflects the real-world value our platform brings to operations teams striving to maximize uptime, perfect their batch quality, and uncover hidden capacity across their enterprises.”

To learn more about TwinThread, contact your TwinThread representative or visit our website.

 

About TwinThread 

TwinThread is the world's first complete Industrial AI Platform built to amplify human expertise and optimize legacy systems. Through Predictive, Prescriptive, Generative, and Agentic AI, we enable operations teams to anticipate issues, accelerate problem-solving, and innovate on a single line or across global operations. With over 1 million digital twins, nearly 50 million sensors, and 2 million AI models deployed, TwinThread is proven to deliver scalable AI, maximize ROI, minimize downtime and provide continuous value.