Normalized claim
Quantified impact: 85%
Serves 85% of the UK grocery retail market.
Mondra Empowers UK Grocers to Slash Supply Chain Emissions with AI Assistant
Use case typeSustainability analyticsUpdated Jun 13, 2026
Mondra, a leader in food supply chain decarbonization, launched Sherpa, an AI-powered assistant built on Azure OpenAI, to help UK grocery retailers assess and reduce the carbon footprint of their products down to the ingredient level. Sherpa enables retailers to interrogate supply chain data via natural language and simulates the impact of sourcing changes on emissions and resilience. The platform automates life cycle assessment at scale, providing actionable data for over 60,000 products and serving 85% of the UK grocery retail market. The solution allows rapid scenario analysis, such as ingredient reformulation or supplier changes, enabling significant carbon savings and supply chain resilience. Key stakeholders include major UK grocers, NGOs, and the UK government. Early results show measurable decreases in product emissions, exemplified by an 18% reduction from a single product reformulation. Sherpa is an industry-first in providing such granular and scalable carbon analytics for grocery supply chains.
- Organization
- Mondra
- Industry
- Retail
- Location
- United Kingdom
- Published
- October 2024
Reported outcomes
−18%
quantified impactSustainability & resources
85%quantified impact
Strategic outcomes
New product / capabilityLaunched AI supply-chain emissions assistantNew product / capabilityEnabled ingredient-level carbon analysisBetter decisions & insightSupports scenario analysis for sourcing decisionsScale & capacityAutomated life cycle assessment at scale
Catalog median for sustainability & resources deployments: −25% across 23 reported metrics. Compare benchmarks →
Why do we believe this?Outcome claims, sources, and evidence checks
Normalized claim
Quantified impact: 18% decrease
Enabled an 18% reduction in product carbon emissions in one reformulation case.
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Mondra
- Provider
- Microsoft
- Maturity
- Scaled Production
- Linked source
- ukstories.microsoft.com
The platform automates life cycle assessment at scale, providing actionable data for over 60,000 products and serving 85% of the UK grocery retail market
Customer identity supportedSource describes one deploymentMaturity supported
Primary read
Use case focus
Showing 3 of 3
- 1Automated Life Cycle Assessment and CO2 Calculation for Retail Products
- 2Scenario Simulation for Ingredient Sourcing and Supply Chain Resilience
- 3AI-Driven Carbon Footprint Analytics for Grocery Retail
- Food retailers face intense pressure to reduce carbon emissions throughout their complex supply chains.
- Measuring and comparing environmental impact for tens of thousands of products is labor intensive and error-prone.
- Sourcing variations and supply chain resilience need to be quantified for better risk management.
- Meeting net zero and regulatory targets requires accurate supply-chain-wide emissions data.
- Developed Sherpa, an AI chatbot built on Microsoft Azure OpenAI, to calculate CO2 emissions down to the ingredient level.
- Integrated Sherpa into Mondra's platform to monitor over 60,000 products and simulate supply chain changes.
- Automated the process of Life Cycle Assessment at scale.
- Enabled retailers to perform scenario analysis easily with natural language queries.
Technologies
- Serves 85% of the UK grocery retail market.
- Enabled an 18% reduction in product carbon emissions in one reformulation case.
- Provides full supply chain visibility for over 60,000 products and one million ingredients.
- Supports data-driven decisions for carbon reduction and supply chain resilience.
Architecture
Sherpa is a chatbot layer built on top of Mondra's supply chain decarbonization platform and leverages Microsoft Azure OpenAI to process queries and simulate supply chain and ingredient-level changes. The platform automates Life Cycle Assessments and integrates with retailer data sources for analytics and reporting at industry scale.
Sources & evidence1
Evidence: Medium50/100Evidence strength
- Customer explicitly identified
- Deployment status explicitly supported
- Quantified outcome available
- Technical implementation details available
Published: Oct 23, 2024Publisher: ukstories.microsoft.com
AI-generated summary. Verify important details with the linked sources before relying on this case.
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