DevPre AI — Mining Fleet Intelligence

[Virtual Presenter] The Mining Fleet Intelligence platform is an advanced system that leverages machine learning algorithms to optimize resource allocation and reduce costs. It provides real-time monitoring and analysis of equipment performance, allowing for swift identification of issues and prompt corrective actions. The platform also offers predictive analytics, which enables operators to anticipate and prepare for future challenges. Additionally, it includes a robust reporting feature that generates detailed summaries of key metrics, facilitating data-driven decision-making. Furthermore, the platform incorporates a user-friendly interface that streamlines communication between teams and stakeholders, ensuring seamless collaboration and information exchange..

[Audio] The situation described is a common occurrence in many industries, particularly in mining operations. A critical piece of equipment fails during a night shift, resulting in significant production losses. The data collected by the Fleet Management System (FMS) provides valuable insights into the equipment's condition, but it often goes unutilized due to lack of intelligence. This scenario highlights the importance of connecting the dots between disparate data points to prevent such incidents. DevPre AI aims to solve this problem by providing real-time intelligence that enables operators to predict equipment failures, manage contractor accountability, and optimize inventory management. By doing so, DevPre AI can help mitigate the financial impact of such failures, which can range from $500000 to hundreds of millions of dollars. Furthermore, the solution addresses broader issues, including the contractor accountability gap and the estimation of production losses rather than precise measurement. By leveraging live demand intelligence, DevPre AI can help bridge the gap between reactive and proactive maintenance, ultimately leading to improved operational efficiency and reduced costs..

[Audio] The solution provided by DevPre AI is based on six specialized AI agents that are designed to operate independently but work together seamlessly. Each agent is focused on a specific area of operations such as fleet management, predictive maintenance, and supply chain optimization. The agents use machine learning algorithms to analyze data from various sources and make predictions about future events. They also have the ability to learn from experience and adapt to new situations. This allows them to provide accurate and timely insights to operators who need to make informed decisions. The agents are able to communicate with each other and share information in real-time, creating a comprehensive view of the entire operation. This enables operators to monitor multiple aspects of their business simultaneously, making it easier for them to identify problems and opportunities. The agents can be integrated with existing systems and technologies, allowing operators to leverage the benefits of AI-powered decision-making. By using these agents, operators can gain a competitive edge over their rivals and improve their overall efficiency..

[Audio] The company has been working on a new project for several years, but it has not yet been completed. The project was initiated by the CEO, who had a vision for a more efficient and effective way of doing things. He wanted to create a system that would allow employees to work independently and make decisions based on their own judgment. However, the project has faced numerous challenges and setbacks, including funding issues and resistance from some employees. Despite these obstacles, the company remains committed to completing the project and has continued to invest time and resources into its development. The CEO's vision for a more autonomous workforce has resonated with many employees, who see the potential benefits of increased productivity and flexibility. Many employees have expressed enthusiasm for the idea of being able to make decisions and take ownership of their work, and some have even started to implement similar systems in their own departments. However, there are also concerns about the potential risks and downsides of such a system. Some employees may feel overwhelmed or undervalued if they are given too much autonomy, while others may struggle with the lack of clear direction and guidance. There are also worries about the impact on teamwork and collaboration, as some employees may prefer to work together rather than individually..

[Audio] The Health and Performance Agent is a critical tool for monitoring the health of your fleet. It continuously processes all FMS telemetry for every truck and generates a composite health score from zero to one hundred. This score reflects the overall condition of each vehicle, taking into account wear indices across twelve key component categories. The agent also surfaces performance deviation alerts whenever a truck's behavior deviates from its baseline, allowing for proactive maintenance. Furthermore, the Health Agent performs shift-over-shift trend analysis, identifying gradual degradation that may indicate impending failure. This enables early detection and prevention of costly repairs. The Predictive Failure Agent builds upon this capability, using machine learning models to predict failure risks for individual components. By integrating these two agents, you can significantly reduce unplanned failures and minimize downtime. The results speak for themselves: a 72% reduction in unplanned failures within the first year, and a 91% success rate in predicting recoverable failures 14 days or more in advance..

[Audio] Automated contract compliance monitoring is a valuable capability that allows companies to monitor their contractual obligations in real-time. This type of monitoring ensures that all maintenance tasks outlined in the contract are completed on schedule. The technology offers numerous benefits, including cost reduction from missed tasks, improved operational efficiency, and increased accountability among contractors. By automating the tracking process, companies can prevent costly disputes and minimize the impact of missed deadlines. The system works by ingesting contracts, validating obligations, and tracking compliance in real-time. Automated notifications are sent to relevant parties, such as the contract management team and contractors, to ensure awareness of any issues or concerns. This approach provides complete visibility into contractual obligations, making it easier to identify areas for improvement and optimize maintenance strategies..

[Audio] The Production Loss Agent accurately calculates the cost of sudden downtime and provides a specific dollar amount for each event. This allows for better financial planning and decision-making. Additionally, the agent gives information about potential risks of downtime, helping to prevent or lessen these events. The Inventory Agent improves inventory management by adjusting reorder points based on real-time failure risk signals, resulting in fewer stockouts and excess inventory. Together, these two agents offer a complete overview of financial performance and support data-driven choices..

[Audio] The potential financial benefits of implementing DevPre AI are highlighted in the table. These benefits include reduced costs associated with unplanned failures, improved PM compliance, decreased emergency spare parts freight, and enhanced demand intelligence. The estimates indicate that significant value can be recovered, with an annual range of $4 million to $14 million depending on the scale of the operation. The provided ROI framework offers a clear view of the expected returns on investment, with an average return of 3.2 times the initial investment in the first year. Additionally, the estimated payback period is approximately 8 months, indicating a relatively short time frame for realizing the benefits of the investment. These findings suggest that DevPre AI has the potential to generate substantial financial gains for organizations, making it a favorable option for consideration..

[Audio] DevPre AI is designed to work with existing systems, without requiring platform replacement, new ERP, or lengthy integration projects. We integrate with your current systems and add an intelligence layer on top. The process is divided into four stages over ninety days. In the first twenty-one days, we establish data connections to your FMS, contractor maintenance system, and inventory platform. Typically, data starts flowing within five business days. From days fourteen to twenty-eight, we upload your commercial maintenance contracts, conduct an LLM extraction, and validate with your team through a few short sessions. By day twenty-eight, all obligations are live. From days twenty-one to forty-five, we calibrate predictive failure models using at least twelve months of site-specific FMS history, with twenty-four months being ideal. Models are validated against known failures before being implemented in the dashboard. Then, from days twenty-eight to forty-five, we optimize inventory levels through a min-max analysis and present the results to your procurement team for approval. The next stage, from days forty-five to sixty, involves going live and handing over the system to your operations and maintenance teams. This includes a full dashboard, all six agents active, and two-day onsite training along with documented runbooks and escalation procedures. The final stage, from days sixty to ninety, involves reviewing and expanding the system. Within thirty days, we provide a report on the value generated by the system, including detected, prevented, and recovered issues. We also refine the models based on observed outcomes and identify opportunities for expansion. This is a targeted consultancy engagement, not a complete transformation program..

[Audio] There are six outcomes that address the direct costs and risks involved in your operation. Each outcome is focused on a specific area where there are potential costs or risks. These outcomes have a direct impact on your operation once the system is up and running. With the system in place, you can expect reduced downtime as it predicts failures and allows for proactive maintenance of trucks before they breakdown. The system also promotes contract transparency by holding contractors accountable to their service level agreements. Additionally, it optimizes inventory management by providing data-driven decisions. Moreover, it enables asset life extension and data-driven decisions through real-time intelligence. Lastly, the system helps improve production recovery by providing the ability to measure and respond to production losses..

[Audio] The company's mission statement is "to empower the world's mines through data-driven decision making". The company's vision statement is "to be the leading provider of fleet management solutions for the global mining industry". The company's values are: - Empowering people - Innovation - Collaboration - Integrity - Excellence - Customer-centricity These values guide our decisions and actions as a company. They are reflected in everything we do, from developing new products to providing customer support..

[Audio] The speaker begins by saying that the company has been working hard to develop a new technology that uses artificial intelligence to analyze data from various sources. This technology allows companies to gain insights into their customers, products, and markets, which can be used to inform business decisions. The speaker explains that the company has developed a unique approach to analyzing data, using a combination of machine learning algorithms and human expertise to identify patterns and trends that may not be immediately apparent. This approach enables companies to make more informed decisions, such as identifying opportunities for growth and optimizing resource allocation. The speaker highlights several examples of companies that have successfully implemented the technology, including a leading manufacturer of automotive parts, a major retailer, and a large financial institution. These companies have seen significant improvements in their operational efficiency, customer satisfaction, and revenue growth. The speaker notes that these companies have achieved these results by leveraging the insights generated by the technology, such as identifying areas of inefficiency and implementing process improvements. The speaker emphasizes that the company's technology is not limited to just analyzing data, but also provides recommendations for action based on those insights. This means that companies can use the technology to not only gain insights, but also to take concrete steps towards improving their operations and driving growth. The speaker concludes by highlighting the benefits of the technology, including improved decision-making, increased productivity, and enhanced customer satisfaction. The speaker invites the audience to join the company in its mission to help businesses like theirs succeed. The speaker notes that the company has developed a range of tools and resources to support businesses in achieving their goals, including a comprehensive platform for data analysis and a team of experts who can provide guidance and support. The speaker emphasizes that the company is committed to helping businesses achieve success, and that the company's technology has the potential to revolutionize the way businesses operate. The speaker ends the presentation by thanking the audience for their attention and inviting them to take part in a discovery engagement to learn more about the company's technology and how it can benefit their business. The speaker notes that the discovery engagement is a free service, with no obligation, and that it provides an opportunity for businesses to experience the benefits of the technology firsthand. The speaker concludes by emphasizing that the company is committed to helping businesses achieve success, and that the speaker hopes that the audience has gained valuable insights from the presentation..