Assessing one product took weeks. Now, an AI copilot models 60,000 items in four hours to simulate lower-carbon recipes.
A software platform serving 90% of UK grocery retailers tracks environmental data for over 60,000 products and one million ingredients.
Generating lifecycle assessments involved manually collecting data from multiple sources, a process that took several weeks or months for a single...
“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.”
Mondra's Product sustainability analysis is part of this use case:
AI-powered supply chain intelligence platform for the food and beverage industry.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Related implementations across industries and use cases
Extracting store insights took data scientists weeks. Now, managers query AI to instantly map foot traffic and spot self-checkout theft.
Young staff hesitated to ask managers, slowing stocking. A text-based AI assistant now answers inventory queries on personal phones.
Checking market share meant waiting for reports. Now, managers ask a Teams AI bot for instant, governed answers.
Checking market share meant waiting for reports. Now, managers ask a Teams AI bot for instant, governed answers.
10,000 supply chain workers spent half an hour manually searching compliance libraries. Now, an AI assistant finds answers instantly.
Store managers lost applicants to a 10-day hiring cycle. Now, an AI agent screens and schedules via text, saving thousands of hours.
Shoppers built lists item-by-item. Now, they build full baskets in one prompt, while staff automate internal workflows.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.
Assessing one product took weeks. Now, an AI copilot models 60,000 items in four hours to simulate lower-carbon recipes.
A software platform serving 90% of UK grocery retailers tracks environmental data for over 60,000 products and one million ingredients.
Generating lifecycle assessments involved manually collecting data from multiple sources, a process that took several weeks or months for a single...
“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.”
Mondra's Product sustainability analysis is part of this use case:
AI-powered supply chain intelligence platform for the food and beverage industry.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Related implementations across industries and use cases
Extracting store insights took data scientists weeks. Now, managers query AI to instantly map foot traffic and spot self-checkout theft.
Young staff hesitated to ask managers, slowing stocking. A text-based AI assistant now answers inventory queries on personal phones.
Checking market share meant waiting for reports. Now, managers ask a Teams AI bot for instant, governed answers.
Checking market share meant waiting for reports. Now, managers ask a Teams AI bot for instant, governed answers.
10,000 supply chain workers spent half an hour manually searching compliance libraries. Now, an AI assistant finds answers instantly.
Store managers lost applicants to a 10-day hiring cycle. Now, an AI agent screens and schedules via text, saving thousands of hours.
Shoppers built lists item-by-item. Now, they build full baskets in one prompt, while staff automate internal workflows.
Repetitive coding slowed R&D. Now 80% of engineers use agentic tools to automate work, saving up to 2 hours weekly per person.
Manual testing consumed 20% of developer time. Now, 1,500 engineers use AI agents to auto-generate tests and prototype solutions.