A gap between climate urgency and corporate decision-making might leave many companies relying on slow, resource-intensive lifecycle assessment that may not be able to keep pace with business needs. Earthster enters this landscape as a cloud-based SaaS platform designed with an aim to eliminate inefficiencies by enabling a broad range of product-specific Life Cycle Assessments (LCA) to be produced quickly and at scale.
With a goal to deliver environmental clarity at speed, Earthster aims to position itself as a fast-evolving tool that can empower sustainability leaders. It's this vision that has directed its founders, Dr. Daniel Collado-Ruiz and Dr. Gregory Norris, whose combined academic and consulting background has shaped Earthster's mission to make every euro or dollar work toward high-impact sustainability decisions.
Collado-Ruiz began his career in academia, spending a decade as an associate professor of eco-innovation, researching how companies interpret environmental data and make sustainability-related choices. His focus on decision quality rather than methodological purity allowed him to conclude that organizations needed insight, not complexity. "Back then, people sought an LCA for a problem," he recalls. "I'd often ask if they had the expertise or data to execute it. If not, I'd argue they would be better off with other tools."
A conversation with Norris after a major event brought both founders back to their research roots. Both Norris and Collado-Ruiz had explored different realms of environmental data usage, and when they joined forces, Collado-Ruiz highlights that the synergy was immediate. "We realized that by combining our strengths, we could reshape how businesses understand their environmental impact," he adds. From there, Earthster became committed to democratizing environmental insight and removing the barriers preventing non-experts from making informed sustainability decisions.
Collado-Ruiz highlights that Norris has brought three decades of experience across LCA academia and consultancy, guiding research teams working on frontier topics ranging from uncertainty modeling to social LCA. Norris' deep modeling expertise complements Collado-Ruiz's user-centric lens, creating a partnership defined by rigorous debate and creative problem-solving.
"We challenge each other based on our backgrounds in a very positive way," Collado-Ruiz explains. "If he proposes a modeling approach, I focus on whether people can make decisions with it, and he does the same in reverse." That balance, he notes, has become the bedrock of the company's philosophy. "We're making Earthster advanced enough for experts yet intuitive enough for cross-functional teams across an organization," he adds.
At the core of their offering is the Earthster LCA software, a fully cloud-based platform where, Collado-Ruiz notes, users can log in from anywhere, collaborate across continents, upload data in bulk from systems like Enterprise Resource Planning (ERP) or Product Data Management (PDM), build new models, and analyze results at scale. According to him, the platform can also support portfolio-level analysis, automated data handling, and seamless export workflows for tasks like preparing Environmental Product Declarations.
"I've often come across organizations performing new assessments, procuring fresh searches for data which may already exist within the company's current database," he says. Earthster aims to remove that friction, allowing specialists, procurement officers, engineers, and even sales teams to contribute their knowledge directly. "We want to make sure that every decision about product sustainability should be made once. If the company has this policy, you do it once, you don't have to reinvent the wheel," he explains. "In this way, organizations can turn sustainability into a shared responsibility rather than a compartmentalized task."
Looking forward, Earthster is working on industry-wide challenges such as data comparability, consistency, and quality. Collado-Ruiz and Norris are active in working with organizations advocating for more standardized, agnostic models that connect product data to the best available environmental background information.
They approach AI with both enthusiasm and caution, aiming to add features that help users verify data quality. This balance, Collado-Ruiz argues, is essential for maintaining trust in environmental data across industries.
"We will succeed when anybody questioning something about sustainability has the answer readily in their hands," Collado-Ruiz says. With its dedication to clarity, Earthster is aiming to build the infrastructure to make that future possible, shaping how modern businesses act on environmental responsibility at scale.
