Mondra Global Limited facilitates transition to net-zero food systems with AI and Microsoft Azure

Mondra Global Limited (Mondra) is revolutionizing how food retailers assess the environmental impact of their products with an innovative AI copilot called Sherpa. Mondra embraced the Microsoft Azure ecosystem to empower clients to uncover new, AI-driven insights with natural-language queries. For food retailers eager to embrace sustainable sourcing practices, Sherpa offers unprecedented visibility into the environmental impact of over 60,000 products and more than 1 million ingredients.

Transitioning to a net-zero food system

Mondra’s mission is to help food retailers improve their environmental impact across supply chains by providing lifecycle assessments (LCA) that assess factors including carbon emissions, water consumption, biodiversity, and land use. On average, food retailers stock about 10,000 unique products with vastly different environmental impacts.

LCA analysis using traditional methods required collecting data by hand from multiple sources and studies; evaluating just one product could take several weeks or months. If that product’s composition subsequently changed, the LCA became obsolete. Mondra adopted big data engineering and AI to harness product data at scale, streamlining LCAs and offering clients an opportunity to discover new data-driven insights.

“If we can deliver automated lifecycle assessment at scale, we can give food producers and retailers the insights into their products so that they could work to improve them collaboratively with their supply base,” says Tom Holden, Chief Product Officer at Mondra.

Empowering clients with AI-driven insights

Mondra recognized the transformative potential of AI and data and began considering solutions that would consolidate data and empower the company with AI-driven capabilities. Mondra turned to the Microsoft Azure data platform and Azure SQL Database Hyperscale to handle the large volumes of data it regularly ingests. “When we process new data, we have a massive amount that needs to go out immediately,” says Marco De Sanctis, Chief Technology Officer at Mondra. “Azure SQL Database Hyperscale was the only tier that allowed us to do a massive data push without affecting the user experience in our platform.” Azure SQL Database Hyperscale has a flexible storage architecture that can manage 10 gigabytes up to 128 terabytes.

Mondra then began developing Sherpa, an AI copilot designed to radically simplify how clients explore and act on environmental data. Built with Azure OpenAI Service and Semantic Kernel, Sherpa answers natural-language questions—such as “Which of my products has the highest carbon footprint?”—with instant, data-backed answers. The copilot combines the natural language capabilities of Azure OpenAI with the vector support in Azure SQL database to uncover AI-driven insights. “Sherpa democratizes access to the system,” says Holden. “For those who aren’t sustainability experts, they can ask a question in their own language and get an answer.”

Monitoring over 1 million ingredients to assess environmental factors

Mondra is pilot testing Sherpa with 10–20 clients in spring 2025. By monitoring data on over 60,000 unique products and over 1 million ingredients, Mondra has slashed the LCA timeline for client requests from several weeks or months to just four hours with hypermodeling AI. This streamlined process has enormous potential to create more sustainable practices with the company’s customer base among UK food retailers in particular. “Ninety percent of UK grocery retailers rely on Mondra, so we are on track to model over 50% of all food in the UK over all customers,” says Holden.

Sherpa provides retailers with an accessible and cost-efficient solution to advance net-zero goals and sustainable sourcing methods. Mondra can produce digital twins of a customer’s supply chain, empowering clients to identify areas for optimization. Clients can also explore how changing ingredient formulation can impact overall carbon dioxide emissions. One customer reformulated a lasagna and reduced the carbon emitted in its production by 18%.