SAN ANTONIO — January 29, 2026
Executive Summary
Frost & Sullivan has awarded Haber its 2025 Global Technology Innovation Leadership Recognition in the Industrial AI category, citing the company’s demonstrated ability to translate artificial intelligence into real-time, closed-loop industrial process control. The recognition highlights Haber’s performance across technology innovation, execution discipline, and measurable industrial outcomes as manufacturing, utilities, and process industries address rising operational complexity and resource constraints. According to Frost & Sullivan, Haber distinguished itself through the deployment of adaptive, self-optimizing control systems that integrate artificial intelligence directly into live production environments. The recognition forms part of Frost & Sullivan’s annual Best Practices framework, which evaluates organizations based on strategy effectiveness and strategy execution across global markets.
Announcement Overview
Frost & Sullivan announced that Haber has received the 2025 Global Technology Innovation Leadership Recognition for Industrial AI, acknowledging the company’s role in advancing artificial intelligence–driven industrial process control. The recognition evaluates Haber’s ability to operationalize AI in real-time manufacturing and utility environments, moving beyond traditional automation approaches toward adaptive, closed-loop systems.
According to Frost & Sullivan, the recognition reflects Haber’s sustained focus on aligning long-term technology strategy with consistent execution in live industrial settings. The assessment considers how effectively organizations translate innovation into measurable operational results, particularly in industries characterized by variable inputs, resource constraints, and increasing performance demands.
The award forms part of Frost & Sullivan’s broader Best Practices Recognition program, which benchmarks companies across regional and global markets using structured analytical methodologies. The program is designed to identify organizations that demonstrate excellence in innovation strategy, implementation rigor, and market responsiveness.
Key Announcement Details
- Announcement type: Industry recognition and technology leadership award
- Awarding organization: Frost & Sullivan
- Recognition: 2025 Global Technology Innovation Leadership Recognition
- Industry category: Industrial AI
- Geographic scope: Global
- Recipient: Haber
- Assessment framework: Strategy effectiveness and strategy execution
- Release date: January 29, 2026
Strategic Context
According to Frost & Sullivan, industrial operators across manufacturing and utilities are navigating increased operational complexity driven by workforce attrition, raw material variability, energy constraints, and heightened sustainability requirements. In this environment, traditional automation systems based on static logic and manual intervention often struggle to adapt to changing process conditions in real time.
Frost & Sullivan’s analysis indicates that industrial AI platforms capable of embedding intelligence directly into production workflows are increasingly relevant as operators seek systems that not only provide visibility but also enable autonomous control and continuous optimization. The firm noted that the ability to integrate advanced analytics with process-domain expertise is a key differentiator as industrial environments demand both reliability and adaptability.
Within this context, Haber was evaluated on its ability to deploy industrial AI solutions that operate continuously in live environments, adjusting process variables dynamically while maintaining transparency and control reliability. According to Frost & Sullivan, this capability aligns with broader industry shifts toward intelligent automation and resilience-driven operations.
Assessment Framework and Evaluation Criteria
Frost & Sullivan evaluates recognition recipients using a benchmarking framework built around two core dimensions: strategy effectiveness and strategy execution. Strategy effectiveness assesses the clarity, relevance, and long-term viability of a company’s innovation roadmap, while strategy execution examines the organization’s ability to deliver scalable, consistent results in operational environments.
According to Frost & Sullivan, Haber demonstrated strong alignment between its strategic vision and execution capabilities. The firm cited the company’s focus on translating artificial intelligence into practical industrial applications, rather than limiting AI deployment to advisory or monitoring roles.
The evaluation also considered how effectively Haber’s solutions address persistent industrial challenges, including operational variability, resource inefficiencies, and the need for rapid decision-making under dynamic conditions. Frost & Sullivan stated that Haber’s approach reflects a shift from static automation toward adaptive control architectures.
Leadership Commentary
“Haber is redefining industrial AI by embedding intelligence directly into production processes, enabling operators to respond proactively rather than reactively, and delivering measurable operational and sustainability outcomes,” said Vijay Mathew, Director, Growth Advisory at Frost & Sullivan.
“As manufacturers and utilities face growing pressure to improve efficiency and sustainability, the ability to operationalize real-time data is becoming essential. Haber’s Industrial AI combines analytics with deep process expertise to support measurable improvements in industrial operations,” said Priya Venkat, Co-Founder and Chief Operating Officer of Haber.
Industrial AI and Closed-Loop Process Control
According to Frost & Sullivan, a key factor in Haber’s recognition is its emphasis on real-time, closed-loop control systems that move beyond conventional automation paradigms. Traditional industrial automation platforms often provide data visibility and alerts but rely on human intervention or predefined logic to adjust processes.
Haber’s industrial AI systems are designed to continuously analyze real-time operational data and autonomously adjust process parameters through closed-loop control. According to the company, this approach enables production environments to stabilize operations, reduce variability, and optimize resource usage under changing conditions.
Frost & Sullivan noted that this model represents an evolution in industrial AI, where intelligence is embedded directly into operational decision-making rather than layered on top as an advisory function. The firm stated that this capability is particularly relevant in industries with complex process dynamics and high sensitivity to input variability.
Platform Architecture and Product Framework
Haber’s innovation is embodied in its Elixa and Mt.Fuji platforms, which integrate plant data, domain expertise, and real-time decision-making into a unified operational framework. According to the company, these platforms connect directly with existing plant infrastructure, enabling seamless integration into live environments.
Unlike traditional automation systems that focus on monitoring and reporting, Elixa and Mt.Fuji are designed to continuously adjust process variables through autonomous control mechanisms. According to Haber, this enables facilities to stabilize production outputs, reduce waste, and improve energy, water, and chemical efficiency.
Frost & Sullivan’s analysis highlighted the platforms’ ability to operate alongside existing programmable logic controllers (PLCs) and supervisory control and data acquisition (SCADA) systems. This modular architecture allows for rapid deployment without requiring wholesale replacement of existing automation infrastructure.
Addressing Industry Challenges
According to Frost & Sullivan, Haber’s technology addresses several persistent challenges facing industrial operators. Workforce attrition has increased reliance on automated systems capable of maintaining performance despite reduced on-site expertise. At the same time, variability in raw materials and operating conditions requires systems that can adapt dynamically rather than rely on fixed logic.
The firm also cited rising pressure on manufacturers and utilities to reduce resource consumption and improve sustainability outcomes. Haber’s industrial AI systems are designed to optimize energy, water, and chemical usage while maintaining production stability.
According to the company, its hybrid intelligence approach combines physics-based process understanding with advanced machine learning techniques. This integration enables scalable deployment across multiple industries while preserving accuracy and operational transparency.
Customer Deployment and Measurable Outcomes
Haber reported that its Elixa and Mt.Fuji platforms have been deployed across more than 100 manufacturing sites globally. According to the company, these deployments have generated over $300 million in annual recurring savings for customers, alongside measurable reductions in chemical usage and water consumption.
Frost & Sullivan noted that the ability to demonstrate quantifiable outcomes is a critical factor in evaluating technology innovation leadership. The firm stated that Haber’s focus on measurable performance improvements differentiates its industrial AI offerings from solutions that emphasize theoretical capability without operational validation.
The company’s modular deployment model enables customers to realize value within weeks rather than months, according to Haber. This approach allows facilities to implement industrial AI incrementally while maintaining continuity of operations.
Market Responsiveness and Scalability
According to Frost & Sullivan, Haber’s customer-centric operating model strengthens its market position by aligning technology development with real-world operational needs. The firm cited operator-first design principles and modular deployment as key enablers of scalability across diverse industrial environments.
Haber’s solutions are designed to support a range of industries, including pulp and paper, food and beverage, and institutional utilities. According to the company, this cross-industry applicability reflects the adaptability of its industrial AI architecture to different process requirements and operating conditions.
Frost & Sullivan stated that this combination of scalability, execution discipline, and outcome-driven design supports Haber’s positioning as an industrial AI provider capable of addressing complex, resource-intensive environments.
Frost & Sullivan Best Practices Recognition Program
Each year, Frost & Sullivan presents its Technology Innovation Leadership Recognition to organizations that demonstrate excellence in innovation strategy and implementation. According to the firm, recipients are selected through a rigorous analytical process that includes benchmarking, interviews, deep-dive analysis, and extensive secondary research.
The Best Practices Recognition program evaluates companies across multiple dimensions, including leadership, technological innovation, customer experience, and strategic product development. The goal is to identify organizations that advance their industries through forward-looking technology and sustained performance.
Frost & Sullivan stated that Haber’s recognition reflects its assessment of the company’s ability to deliver practical industrial AI solutions that translate innovation into operational value.
About Haber
Haber develops industrial AI software, autonomous process control systems, and advanced process analyzers for manufacturing, utilities, and water systems. The company’s platform deploys purpose-built AI agents that integrate real-time operational data with advanced analytics and machine learning to enable autonomous control and performance optimization in complex environments.
Haber’s solutions support efficiency improvements, resource and energy reduction, and quality enhancement across industries including pulp and paper, food and beverage, and institutional utilities. With deployments across global operations, the company supports customers in transitioning from reactive operations toward intelligence-driven decision-making.
Media Contact
Tarini Singh
Source Attribution
Source: Company announcement
