Hortifrut Optimizes Distribution of Blueberries with AI
Customer Company Size
Large Corporate
Region
- America
- Asia
- Europe
- Africa
Country
- Chile
- Argentina
- China
- Mexico
- Morocco
- Peru
- Spain
- United States
Product
- H2O Driverless AI
Tech Stack
- Machine Learning
- Natural Language Processing (NLP)
- Feature Engineering
- Time Series Analysis
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Productivity Improvements
- Customer Satisfaction
Technology Category
- Analytics & Modeling - Machine Learning
- Analytics & Modeling - Predictive Analytics
Applicable Industries
- Agriculture
Applicable Functions
- Logistics & Transportation
- Quality Assurance
Use Cases
- Predictive Maintenance
- Supply Chain Visibility
Services
- Data Science Services
About The Customer
Hortifrut, based in Chile, is the largest producer of blueberries in the world and operates farms in Peru, Chile, Mexico, Argentina, the United States, Spain, Morocco, and China, with distribution of fruit across 37 countries. Hortifrut addresses 25% of the world blueberry market and is using Driverless AI to make distribution decisions across their expansive operations. They are able to predict the quality of the blueberries from origin to final destination, increasing the consumer experience, and increasing revenue.
The Challenge
Transporting fruit from the farm may take weeks, so Hortifrut had to predict the quality of produce upon arrival. Not being able to do this accurately can impact customer experience and revenue loss. But getting such predictions accurately can be a difficult task given the complexity of the distribution channel, weather data, variety of datasets, shipping times and more. If traditional machine learning methods and toolkits were used, it could easily take months to build accurate predictions that can be reliably deployed. This may also require hiring additional data science talent on the team, hence requiring additional time and budget to achieve the aforementioned business goal.
The Solution
Hortifrut leveraged Driverless AI in order to have better predictive insights into the quality of their blueberries. They used capabilities such as feature engineering, natural language processing (NLP), explainability, timeseries, visualization and scoring pipelines in Driverless AI. Hortifrut is now able to scale their data science efforts in order to deliver use cases such as predicting the quality of blueberries based on features such as variety, farm origin, shipping time, vessel and packaging, without hiring additional data science talent in the team.
Operational Impact
Quantitative Benefit
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