Algo8 Announces Chemelex (Brookfield) Investment and David Prystash Joins Advisory Board 

Vancouver, BC

Algo8 Industrial AI, a leading provider of enterprise AI solutions for industrial sectors, is pleased to announce a strategic investment of US$2 million (approximately C$2.7 million) from Chemelex LLC, which is owned by Brookfield’s private equity business. 

In connection with the investment, David Prystash, Chief Executive Officer of Chemelex, will join Algo8’s Advisory Board, further strengthening the Company’s strategic alignment with global infrastructure and industrial leaders. 

The investment marks a significant milestone in Algo8’s expansion across North America and reinforces its position as a next-generation industrial AI platform delivering measurable operational improvements for large-scale enterprises. 

Chemelex, a global solutions provider backed by Brookfield, brings deep expertise in infrastructure, industrial operations, and large-scale asset optimization. The investment reflects growing demand for advanced AI-driven automation and predictive systems across critical industries. 

Algo8 will deploy the capital to accelerate product development of its proprietary AI platform, PlantBrain, expand its commercial footprint in the United States, and deepen integrations with key enterprise clients in sectors including manufacturing, energy, and infrastructure.

“This investment from Chemelex is a strong validation of the value Algo8 is delivering to industrial enterprises globally,” said Nandan Mishra, Chief Executive Officer of Algo8.

“Having David join our Advisory Board brings invaluable operational and strategic expertise from one of the world’s leading infrastructure platforms. We view this partnership as a catalyst to scale our deployments and drive meaningful efficiency gains across large, complex operations.” 

The relationship between Algo8 and Chemelex builds on existing commercial engagement, where Algo8’s AI systems have demonstrated tangible improvements in operational performance, cost optimization, and predictive maintenance capabilities. 

“Algo8 represents a new generation of industrial AI companies capable of delivering real- world impact at scale,” said David Prystash ,Chief Executive Officer of Chemelex.

“We have been highly impressed with the performance of Algo8’s technology in live environments. Joining the Advisory Board allows us to further support the Company’s growth while advancing digital transformation across industrial and infrastructure assets globally.” 

As part of the broader strategic relationship, the parties intend to collaborate on identifying and deploying AI-driven solutions across Chemelex’s customers and affiliates globally, further accelerating Algo8’s access to large enterprise customers. 

Prof. Ashutosh Sharma, Padma Shri Awardee, Joins Algo8 Global Advisory Board 

New Delhi | Houston | Toronto

Algo8 AI, a global Industrial AI and sustainability intelligence company, announced that Prof. Ashutosh Sharma, a Padma Shri awardee and Institute Chair Professor at IIT Kanpur, has joined its Global Advisory Board. 

In his role as an advisor, Prof. Sharma will provide strategic guidance on building scalable, governance-aligned Industrial AI platforms, with a focus on integrating ESG principles, strengthening industry–academia collaboration, and supporting Algo8’s long-term growth strategy in global capital markets. 

“We are honored to welcome Prof. Ashutosh Sharma to our Global Advisory Board,” said Nandan Mishra, Co-founder & CEO of Algo8 AI.

“His experience in building national research ecosystems, strengthening industry–academia partnerships, and translating scientific innovation into real-world systems aligns strongly with our long-term platform vision. His guidance will help us develop responsible and scalable Industrial AI systems integrated with ESG and governance frameworks.” 

Prof. Sharma is Institute Chair Professor at IIT Kanpur and previously served as Secretary, Department of Science & Technology, Government of India, where he played a key role in strengthening national research systems, translational R&D frameworks, innovation programs, and industry–academia partnerships. He was awarded the Padma Shri for his contributions to science and public service. 

“I am pleased to join the Algo8 Global Advisory Board,” said Prof. Ashutosh Sharma. “Strong innovation systems require alignment between science, industry, institutions, and governance. Industrial AI can support productivity and sustainability together when developed through structured and responsible frameworks.” 

The appointment further strengthens Algo8’s institutional foundations as it continues to build durable, ESG-integrated and governance-aligned Industrial AI infrastructure for long-term value creation in global public markets. 

Algo8 Launches Dutch Entity to Drive Industrial AI Across Europe

Breda, Netherlands / London, UK

Algo8 UK, a global Industrial AI leader, has launched its Dutch subsidiary, Algo8 Netherlands B.V., to power Europe’s energy and manufacturing transformation through cognitive automation.

“Industrial AI is now mission-critical to Europe’s green and digital future,” said Nandan Mishra, Founder, Algo8. “Our Dutch base enables real-time, intelligent operations at scale.”

Headquartered in Breda

The new entity will:

• Deliver Algo8’s flagship platform PlantBrain across the EU.
• Forge strategic partnerships in energy, process, and discrete manufacturing.
• Launch a regional AI Lab to build future-ready industrial intelligence.

“We’re not coding dashboards. We’re building thinking machines for the shop floor.” said Himanshu Ujjawal Singh, Co-founder & CTO.

The expansion will be led by Ajay Mishra, Founder & CEO, Algo8 EU.

“Europe is ready. We’re here to make Industrial AI real — from control rooms to boardrooms.”

Prof. Luk Van Wassenhove, INSEAD professor and advisor to Algo8 EU, added:

“Industrial AI must drive resilience, not just automation. Algo8 is positioned for impact.”

About Algo8

Algo8 is redefining industrial performance with its cognitive platform PlantBrain, deployed across energy, chemical, and manufacturing enterprises. With entities in the USA, Canada, UK, India, and now the Netherlands — Algo8 is building the Cognitive Operating System for Industry.

Press & Media: press@algo8.ai | www.algo8.ai

Algo8.AI Collaborates with Intel to Optimize Task Management with Advanced LLM Solutions

Algo8.AI is proud to announce its successful collaboration with Intel to enhance the performance of our fine-tuned Large Language Model (LLM). This collaboration has enabled us to significantly improve the efficiency of our task management processes across multiple departments, including IT, HR, Customer Support, and Operations. Leveraging the power of LLMs, we have automated the classification and handling of tasks, addressing the challenges posed by the current manual and error-prone system.

Project Overview

Our solution automates the task classification process, categorizing tasks into predefined categories: routine, non-routine, and undefined. This automated classification reduces the time and effort required for manual sorting and ensures accurate task handling across various departments. Additionally, the application enhances data extraction from project documents, providing stakeholders with key insights and summaries, thus improving project interaction management.

Key Features and Use Cases

1. Task Classifier: Automatically categorizes tasks into routine, non-routine, and undefined categories, optimizing the task management process and reducing manual workload.
2. Data Extractor: Extracts essential data from project documents, enabling better information retrieval and improved handling of project interactions.
3. Interaction Follow-Up: Automates follow-up communications through emails and chatbots, ensuring smooth and timely project interactions and documentation.
4. Summary Generator: Generates concise summaries of key documents and interactions, helping stakeholders stay informed and up-to-date on project progress.

Scalable Integration

The solution is designed to be deployed as a scalable application that integrates seamlessly with the organization’s existing project management systems. This ensures streamlined task handling and improved efficiency across departments, while also providing the flexibility to adapt to evolving project requirements.

Optimization on Intel Architecture

To maximize performance and efficiency, the automates the task classification has been meticulously optimized for Intel Architecture, leveraging the advanced capabilities of Intel’s OpenVINO Toolkit. This optimization ensures the automates the task classification fully utilizes Intel’s hardware, resulting in faster processing times, reduced latency, and increased throughput for AI workloads.

The optimization process included enhancing model precision and leveraging Intel’s powerful CPUs to improve efficiency and versatility across various deployment scenarios. The solution has been optimized on 4th Generation Intel® Xeon® Scalable Processors, known for their robust performance and reliability. These processors offer an extensive ecosystem of tools and libraries that streamline AI solution development and deployment, making them an ideal choice for the automates the task classification.

Collaboration with Intel

Our partnership with Intel played a crucial role in optimizing the performance of our LLM model as they provided us with a virtual machine (VM) on their servers to test the performance and throughput of our models.. By utilizing Intel’s cloud platform and integrating their OpenVINO toolkit, we achieved a significant improvement in model performance. The processing time was drastically reduced when using OpenVINO’s FP16 optimization, leading to faster and more accurate results. This collaboration not only enhanced the model’s efficiency but also demonstrated the potential of combining cutting-edge AI technologies with Intel’s powerful optimization tools.

Conclusion

The collaboration between Algo8.AI and Intel has successfully transformed our task management processes, showcasing the potential of AI and LLMs in automating and improving business operations. We look forward to exploring further opportunities with Intel to continue innovating and delivering advanced solutions to our clients.

AI Insights Unveiled: Nandan Mishra, Algo8 CEO, Explores AI’s Evolution on News9

Courtesy – NEWS9 Live

Algo8 AI is proud to share a recent feature on our Founder and CEO, Nandan Mishra, in a dynamic discussion hosted by News9. The conversation, which delves into the global and Indian landscape of artificial intelligence, highlights key insights from thought leaders in the field. The discussion explores the milestones achieved in AI, the current state of affairs, and the road ahead. Nandan Mishra’s participation alongside distinguished guests such as Umakant Soni and Pranav Pai emphasizes Algo8 AI’s influential role in shaping the future of AI. The discussion provides valuable perspectives on the evolving landscape of artificial intelligence.

About Algo8

Algo8 is a leading provider of Industrial AI solutions. The company’s platform uses machine learning and artificial intelligence to help energy and manufacturing companies improve their operations, reduce costs, and increase sustainability.

Prof Emeritus Luk Van Wassenhove of INSEAD Joins Algo8 EU/UK Advisory Board

London

Algo8, a leading provider of Industrial AI solutions, announced that Professor Emeritus Luk Van Wassenhove of INSEAD, a renowned expert in operations management, has joined its Advisory Board for Algo8 Europe.

In his role as an advisor, Prof. Van Wassenhove will provide strategic guidance on operations and technology management, growth, and expansion plans.

“We are honored to welcome Prof. Van Wassenhove to our Advisory Board,” said Ajay Mishra, CEO of Algo8, Europe. “His expertise in operations management and his deep understanding of the energy and manufacturing industries will be invaluable to us as we continue to grow and expand our business.”

Prof. Van Wassenhove is a Professor Emeritus of Technology Operations Management at INSEAD, where he holds the Henry Ford Chaired Professorship in Manufacturing, as emeritus. He is Fellow of the Production and Operations Management Society (POMS 2005). In 2006, he received EURO’s Gold Medal. He is Distinguished Fellow of the Manufacturing and Services Operations Management Society (MSOM 2009). In 2018 he was elected Fellow of Institute for Operations Research and the Management Sciences (INFORMS).

“I am excited to join the Algo8 Advisory Board,” said Prof. Van Wassenhove. “I believe that the company has the potential to revolutionize the way energy and manufacturing companies operate. I am looking forward to helping them achieve their goals.”

About Algo8

Algo8 is a leading provider of Industrial AI solutions. The company’s platform uses machine learning and artificial intelligence to help energy and manufacturing companies improve their operations, reduce costs, and increase sustainability.

Predicting Power Requirement In Steel Manufacturing (EAF)

Problem

In the steel manufacturing industry, Electric Arc Furnace (EAF) and Ladle Refining Furnace (LRF) processes require substantial electrical power, supplied by captive power plants (CPPs). Striking a balance between power supply and the manufacturing demand is a complex task due to the variable nature of manufacturing processes and environmental factors. This often leads to surplus power generation, also known as “infirm power”.​

The challenge lies in aligning the power production of CPP with the fluctuating power demand of EAF and LRF. Factors such as the mix of raw materials, atmospheric conditions, and availability of material and assets for subsequent processes complicate this task. Additionally, the limited ramp-up or ramp-down time for power production in CPP can be longer than the 5-minute lead signal provided by the steel plant.

Approach

• Creating a 2-D digital map of the production process​
• Developing data connectors and pipelines for real-time and historical data integration​
• Creating a real-time dashboard for monitoring KPIs & material and equipment availability​
• Developing an AI based dynamic scheduling tool and  demand forecasting​
• Real time alerts by predicting power consumption and risks of schedule delays​

Benefits

• Improved Forecasting: Predict heat start and end times with a lead time of up to 10 minutes
• Reduced Surplus Power​: Reduced surplus infirm power production from 15 MW to 5 MW, leading towards zero​
• Cost Savings​: Savings of approx. $2 Million per year due to reduced infirm power​
• Power Production Alignment​: With improved forecasting, power production aligns with power demand​
• Operational Efficiency: Predictive insights reduced reactive decision-making causing inefficiencies​

Real-Time Visual Inspection of Ingot Defects for the World’s Second Largest Integrated Zinc-Lead Producer

Problem

The world’s second-largest integrated zinc-lead producer faced significant challenges with its ingot production process. With a high production rate of 600 ingots per hour, manual quality control (QC) became impractical and hazardous for workers. The company needed a solution to efficiently and safely inspect ingots for defects in real-time. 

Approach

To overcome the challenges, the company implemented an automated system using cutting-edge computer vision technology. The system was designed to capture defects at high speed, enabling real-time tracking of ingots. Leveraging SAP Business Technology Platform (BTP), a cloud-based deployment, the company ensured seamless scalability and integration with its existing infrastructure. 

Benefits

• Real-Time Defect Tracking: The implementation of the automated system allowed for real-time defect tracking, enabling immediate corrective actions to be taken. 
• Improved Insights: The system provided enhanced insights into raw material quality and production processes, leading to better control over operations and improved efficiency. 
• Live Link with Finished Goods: The solution established a live link with finished goods issuance, optimizing supply chain management and ensuring timely delivery of high-quality products to customers. 
• Enhanced Safety: By eliminating the need for manual quality control, the company improved worker safety in the ingot production process. 
• Increased Productivity: The automated system streamlined the inspection process, resulting in increased productivity and reduced inspection time. 

Overall, the implementation of the automated system with computer vision technology brought significant improvements in ingot quality control, safety, and production efficiency for the zinc-lead producer.

Streamlining Manufacturing Efficiency – Autonomous Production Planning & Scheduling

Problem

Many manufacturing companies face challenges with their manual production scheduling processes, leading to limited capabilities in handling complex multi-layer constraints and resulting in inefficiencies and suboptimal productivity. Static schedules often fail to accommodate changes in demand, machine breakdowns, or material availability, causing wasted resources and reduced productivity. Human errors in manual scheduling can lead to production delays and resource wastage. Moreover, limited visibility into the production process hinders the identification and resolution of bottlenecks. 

Approach

To streamline manufacturing efficiency and optimize production planning and scheduling, the company adopts Algo8’s PlantBrain platform. The platform employs advanced algorithms and machine learning techniques to analyze real-time data from various sources, including production equipment and sensors. This enables the platform to provide intelligent recommendations for production planning and scheduling, leading to improved operational efficiency and better handling of unexpected events. 

Key Features Provided by PlantBrain

• Single Source of Truth (SOP/UI): The platform extracts data from a single source of truth for daily operations, ensuring data consistency and accuracy. 
• Live Dashboard: The platform offers a live dashboard with continuous analysis of planned vs. actual production, providing real-time insights into deviations and performance. 
• Production Variance Analysis: Insights related to deviations between planned and actual production enable the company to identify root causes of delays and take appropriate actions. 
• Inventory Management: The interactive dashboard displays the number of units clear to build based on current and promised inventory levels, helping optimize inventory allocation. 
• Multi-SKU Inventory Allocation: The platform features a generative sub-assembly routine that recommends inventory allocation for cases involving multiple SKUs, optimizing resource utilization. 
• Department-Level Analytics: Production planning analytics at the department level help identify areas for improvement and optimization. 
• Shortfall/Wastage Estimation: The platform estimates potential shortfalls and wastage, enabling proactive measures to minimize material waste and maximize resource utilization. 

Benefits

By deploying PlantBrain for autonomous production planning and scheduling, the manufacturing company gains several benefits:

• Enhanced Efficiency: Algorithm-driven scheduling streamlines production processes, leading to improved overall operational efficiency. 
• Real-time Insights: The live dashboard and continuous analysis provide real-time insights into production performance, enabling proactive decision-making. 
• Optimized Resource Allocation: Intelligent recommendations for inventory allocation and multi-SKU cases optimize resource utilization and reduce material wastage. 
• Minimized Delays: Proactive identification of deviations helps address root causes promptly, minimizing production delays and disruptions. 
• Reduced Human Errors: Automation reduces human errors inherent in manual scheduling, improving production accuracy. 
• Improved Productivity: With better visibility and optimization, manufacturing companies can achieve higher productivity levels. 
• Enhanced Profitability: Streamlining manufacturing efficiency and reducing resource wastage ultimately lead to enhanced profitability for the company. 

By leveraging Algo8’s PlantBrain platform, the manufacturing company achieves more efficient and dynamic production planning and scheduling, leading to cost savings, increased productivity, and improved overall performance.

Safety, Security & SOP Compliance in Manufacturing

Problem

Safety and security are paramount in the manufacturing environment, where numerous hazards pose risks of accidents, injuries, and even fatalities. Manufacturing companies face several challenges in ensuring the safety, security, and compliance with standard operating procedures (SOPs): 

• Protecting Workers: The primary goal is to provide a safe and healthy work environment for employees, minimizing the risk of workplace injuries and illnesses. 
• Reducing Costs: Ensuring safety measures can lead to a reduction in workers’ compensation claims, lost productivity, and potential legal liabilities arising from accidents. 
• Improving Productivity: When workers feel safe and secure, their focus and engagement in work improve, leading to increased productivity. 
• Meeting Regulations: Compliance with safety regulations and industry standards is crucial to guarantee the well-being of workers and the overall manufacturing process. 

Applications

To address the challenges and ensure safety, security, and SOP compliance in the manufacturing environment, several applications can be deployed: 

• PPE Kit Detection: Real-time detection of Personal Protective Equipment (PPE) ensures that employees are wearing the necessary gear, preventing workplace injuries, illnesses, and deaths. 
• Prohibited Actions Detection: Artificial intelligence can be used to detect and alert on prohibited activities such as smoking cigarettes or other hazardous behaviors. 
• Lighting Level Control: Monitoring and controlling lighting levels reduce risks associated with working at night or in loading and unloading zones. 
• Head Counting: Implementing technology for head counting helps identify the number of people present on the shop floor, ensuring compliance with occupancy limits and tracking personnel during emergencies. 
• Hazard Detection: Machine learning algorithms can be trained to detect and alert security personnel when someone enters a restricted or hazardous area, preventing unauthorized access and potential accidents. 
• Access Control: Computer vision technology can be utilized to control access to secure areas of the manufacturing facility, ensuring only authorized personnel can enter sensitive zones. 

Approach

The approach involves deploying various sensors, cameras, and AI-driven technologies to continuously monitor the manufacturing environment for safety and security compliance. Machine learning algorithms are trained on historical data and real-time inputs to identify and respond to potential hazards and security breaches.

Benefits

The adoption of safety, security, and SOP compliance measures in manufacturing brings significant benefits: 

• Worker Safety: By implementing real-time safety measures, the risk of workplace accidents and injuries is significantly reduced, ensuring the well-being of employees. 
• Cost Savings: Reducing accidents and injuries results in lower workers’ compensation claims and associated costs, leading to cost savings for the manufacturing company. 
• Productivity Enhancement: A safe and secure work environment fosters higher employee engagement and focus on tasks, leading to improved productivity and efficiency. 
• Regulatory Compliance: Meeting safety regulations and SOPs ensures compliance with legal requirements and industry standards, mitigating potential penalties and legal liabilities. 
• Emergency Response: Early detection of hazards and access control measures improve the facility’s ability to respond promptly during emergencies, enhancing overall safety and security. 
• Loss Prevention: Preventing prohibited actions and unauthorized access helps in preventing losses due to security breaches and potential theft or vandalism.

By investing in safety, security, and SOP compliance measures, manufacturing companies can protect their workforce, reduce costs, improve productivity, and maintain compliance with regulations, creating a safer and more efficient manufacturing environment.