Industry
Technology
Company Size
51 - 200 employees
Project
Length 7 months
Team Size
3.2 FTE
Data Science
AutoML
MLOps
Machine Learning
Python Kubernetes
FastAPI Kubeflow
KServe AWS
ScikitLearn Tensorflow
At a fast-paced technology company, the product owners have a long list of backlogs driving high demand of the data scientists attention. The complex technology landscape and disparate data systems create a high friction environment for the data scientists to efficiently creating insights and models. The average time from a problem to deployment takes 3+ months, resulting in the business losing competitive edge.
Data scientists lack the bandwidth to support all business use cases. This is compounded by the complex development & deployment environment, resulting in frustrated business & technical team.
The platform allows the users to upload a dataset, create analysis and data transformation, run AutoML using state-of-the-art machine learning algorithms and deploy the model into production.
💰
20% cost reduction in operational cost in deployed machine learning
🕑
Time saved for data scientist in deploying models into production
🚀
Increased collaboration between business users & technical team