Компания EnviTrace получила лидерство над проектом RAIN в рамках федеральной инициативы Genesis Mission

EnviTrace, a firm that provides artificial intelligence software and services for what it bills as “high-stakes subsurface decision-making,” has been one of the more notable additions to Santa Fe’s growing high-tech sector in recent years. Trais Kliphuis and Velimir “Monty” Vesselinov co-founded EnviTrace five years ago. Trais, the CEO, brings more than 30 years of experience in environmental management, regulatory compliance, public-sector program leadership and business development to the job. Monty, EnviTrace’s chief technology officer, has 40 years of experience in computational earth science and artificial intelligence, including 23 years at Los Alamos National Laboratory. He earned a doctorate from the University of Arizona and previously was a tenured professor in hydrogeology in Sofia, Bulgaria. SmartTensors, an AI platform he helped develop, won a 2021 R&D 100 Award and a bronze Market Disruptor honor. Now, their firm has been chosen to lead Project RAIN, part of the massive federal Genesis Mission initiative that also includes such New Mexico entities as Los Alamos National Laboratory, New Mexico State University and the University of New Mexico. The $800 million U.S. Department of Energy undertaking is charged with connecting supercomputers, quantum systems and artificial intelligence. The New Mexican recently submitted several questions to Kliphuis and Vesselinov about their leadership of EnviTrace and the company’s evolution. Some of their responses have been edited for clarity and style. Question: How long has your company been around, how would you describe the work you do and what kind of companies or entities are your clients? Answer: EnviTrace was founded in Santa Fe in 2021, building on decades of work in computational earth science, hydrology, artificial intelligence and applied mathematics. We develop AI tools that help decision-makers understand the subsurface — how water moves, where geologic resources may be found and how confident they can be in those predictions. Our technology analyzes diverse datasets and identifies relationships conventional methods may miss. We combine machine learning with physics-based modeling, information theory, geospatial analysis and uncertainty quantification to produce meaningful results. Our work supports water resources, geothermal energy, critical minerals, environmental remediation and carbon storage. We collaborate with agencies, national laboratories, universities and private organizations. As a Santa Fe company, we are committed to technologies that benefit New Mexico through water management, energy development, environmental protection and resource use. Question: EnviTrace is leading the Project RAIN initiative for the U.S. Department of Energy’s Genesis Mission in partnership with Oak Ridge National Laboratory, Lawrence Berkeley National Laboratory and the University of California-Davis. Is this the largest project EnviTrace has ever been involved in, and what kind of challenge does it present to your company? Answer: RAIN is not our largest project by dollar value, but it may be our most strategically important. We have previously managed larger projects in terms of duration and investment, which also involved national laboratories and research universities; these projects also tackled critical environmental issues such as groundwater contamination, induced seismicity, geothermal exploration and production, energy extraction and storage. These capabilities are part of our existing commercial software and consulting services. What is particularly exciting is that RAIN is our first project under the U.S. Department of Energy’s new Genesis Mission. The Genesis Mission is a historic national initiative led by the Department of Energy, which is building the world’s most powerful integrated science discovery platform. By uniting government, industry, academia and philanthropy, it is accelerating breakthroughs in energy, scientific discovery and national security through a new platform that combines AI, supercomputing, quantum systems and advanced scientific instruments. The challenge is bringing data, models and computing resources from multiple institutions together in one reproducible, scalable scientific system. Question: Why do you think EnviTrace was chosen to lead Project RAIN? Answer: Water flows like everything else. It doesn’t stop at the boundaries we draw between a raindrop, river and aquifer, yet our datasets and models often do. EnviTrace uses AI to bring complex earth-science data together into defensible predictions and decisions — to “Look Deeper,” as our tagline suggests. DOE would need to address its selection process, but the competition was exceptionally strong: More than 5,000 submissions were received — the largest response to a funding opportunity in DOE history — and only 19 of the 278 selected projects are company-led. RAIN uses Information Theory to identify which data improves predictions, where gaps remain, how uncertainty spreads and when added model complexity helps — or simply creates noise. These methods are combined with AI, hydrology, physical modeling, geospatial analysis and uncertainty quantification to improve prediction of connected surface-water and groundwater systems. Question: Do you think EnviTrace’s work on this initiative has the potential to be a defining or even transformative event for your company? Answer: Yes, because the underlying technology has applications far beyond a single water project! The goal of the Phase I [Request for Applications] awards is to identify promising pathways toward transformative scientific capabilities and establish a foundation for future investment and scale. That is closely aligned with the technology EnviTrace has been developing for years. If RAIN demonstrates methods that can improve prediction of complex water systems, many of the same capabilities can be applied to geothermal exploration, critical minerals, produced-water management, environmental remediation, carbon storage and other subsurface problems. That opportunity is especially relevant in New Mexico, where water, energy, minerals and subsurface resources are central to the economy. Decisions about where to explore, drill, develop resources, manage water or remediate contamination can involve very large investments. Better subsurface information and uncertainty analysis can improve those decisions and reduce risk. Question: Please describe how you see your work unfolding as your lead this initiative — have you established a schedule for how long the project is expected to take, developed a plan for how the work will be divided and identified what a successful result would look like? Answer: Phase I runs from September 2026 through May 2027, with a formal review after six months. The project has defined objectives, partner responsibilities, milestones and deliverables. EnviTrace leads overall execution, bringing together contributions from partners with expertise in hydrology, scientific computing, AI, information theory, physics-based modeling and uncertainty analysis. The work begins in the Colorado River Basin, where we are evaluating a physics-informed AI framework for understanding surface-water and groundwater interactions. Success will mean demonstrating better predictions, clearer uncertainty and a foundation for broader use. The larger goal is to give communities and decision-makers a clearer view of the water systems they depend on — and stronger footing for the choices ahead. Links below are provided by a third-party ad network (RevContent). This publication does not endorse or guarantee the products, services, or claims featured.