Case Study: Pastel achieves up to 80% reduction in data preparation time with Datasaur

Pastel Reduces Data Preparation Time by up to 80%

Pastel, an AI enterprise solutions provider focused on financial applications across Africa, was struggling with slow, error-prone manual NLP labeling that limited scalability and project timelines. They selected Datasaur and its NLP labeling automation suite—including ML‑Assisted Labeling, LLM Labs, and Predictive Labeling—using Datasaur’s AWS‑hosted platform with Amazon S3 integration to streamline data ingestion and project setup.

Datasaur deployed its automation tools, an intuitive UI that enables two‑click Predictive Labeling, and dedicated onboarding/support to integrate Pastel’s workflows. As a result, Pastel cut data preparation and labeling time by up to 80%, improved tracking and review processes, increased labeling accuracy and efficiency, and scaled their annotation operations thanks to Datasaur’s platform and support.

Pastel