Global Citrus Company
Consistent and reliable machine learning solutions
Through an MLOps methodology, Baufest accelerated the production deployment of AI models, strengthening their monitoring, traceability, and ability to evolve continuously.
- Industry
- Capabilities
- Topics
- Regions
- 🇦🇷 Argentina
- Published
- July 2026
The Challenge
The company needed a methodology to deploy its machine learning solutions into production more efficiently, reducing delays during deployment while enabling continuous monitoring of the deployed model's prediction accuracy.
The Solution
Using a computer vision–based fruit maturity classification model as an example to transfer the methodology, we assembled a team of IT Operations and Applied AI professionals to implement the full MLOps lifecycle using Azure Machine Learning Studio.
Benefits
- Greater control over model and dataset versioning
- Automated training and deployment through pipelines
- Continuous model monitoring to identify when retraining is needed
- Methodology applicable across any cloud platform