Noitso accelerates model deployment from days to hours
Customer Company Size
SME
Region
- Europe
Country
- Denmark
Product
- Seldon Deploy
Tech Stack
- Python
- Containers
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Productivity Improvements
- Digital Expertise
Technology Category
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Finance & Insurance
Applicable Functions
- Business Operation
Use Cases
- Predictive Quality Analytics
- Predictive Replenishment
Services
- Data Science Services
- Software Design & Engineering Services
About The Customer
Noitso is a company based in Copenhagen, Denmark, founded in 2007. They specialize in data science, data collection, and predictive analysis. Their mission is to use data science and AI to provide their customers with credit ratings, scorecards, and risk profiles. Their customers have use cases ranging from inferring budgets and credit rating, to enterprise data management and scorecards with machine learning used to capture high-risk events. They aim to make vital business decisions accurately using their dynamic solutions to work with big data and AI.
The Challenge
Noitso, a company based in Copenhagen, Denmark, specializes in data science, data collection, and predictive analysis. They provide their customers with credit ratings, scorecards, and risk profiles using data science and AI. However, they faced challenges in deploying their models. The models took a long time to get to production and lacked explainability and monitoring. They were unable to determine when models needed to be retrained, and had to do it after a fixed period of time rather than when necessary. This approach was the only way to maintain accurate predictions and prevent issues such as data drift.
The Solution
Noitso introduced Seldon Deploy to their MLOps stack to improve their model deployment process. Seldon Deploy is a machine learning deployment platform that allows data scientists to deploy, scale, and monitor models in production. With Seldon Deploy, Noitso was able to deploy their machine learning models faster and more accurately. The platform also provided them with the necessary tools to manage code and collaborate with data-savvy colleagues. As a result, Noitso was able to impress their existing customers with faster and more accurate AI, and they plan to roll out this new approach to more customers soon.
Operational Impact
Quantitative Benefit
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