Case Study: ClevAir achieves faster, scalable client onboarding with Addepto's automated data classification

ClevAir speeds onboarding with Addepto using automated data classification

The customer, ClevAir, delivers a smart system for managing building energy consumption. Their challenge was a manual data labeling process that slowed client onboarding and limited scalability, as their engineers had to clean and annotate large volumes of unlabeled, inconsistent data from heterogeneous sources. Addepto was engaged to provide AI consulting to automate this process.

Addepto implemented a machine learning solution for automated semantic data type detection, which was robust to dirty and unstructured data. This system, built for scalability in an AWS environment, replaced manual rules and outperformed traditional approaches. As a result, ClevAir achieved faster client acquisition and improved business scalability by enabling automatic data cleaning and a smooth, error-free pre-optimization process for new customers.

ClevAir