Case Study: Adarga achieves 10–12x faster unstructured-data processing and reproducible MLOps with Pachyderm

How Pachyderm Is Used to Support Adarga in Analyzing Huge Volumes of Information

Adarga, a London-based AI software developer, faced the challenge of processing and extracting intelligence from vast volumes of unstructured data while developing, training and scaling ML models reliably. To address needs for data consistency, lineage and scalable MLOps, Adarga selected Pachyderm and its data-driven pipelines and versioning capabilities as a core part of its MLOps stack.

Pachyderm provided pipeline-based data versioning, incremental processing, parallelization and autoscaling, giving Adarga repeatability, traceability and smoother migration from experimentation to production. The solution enabled ML governance across training-to-production, sped up preprocessing (a reported 10–12x reduction in processing time — finishing jobs in about 20 minutes), and improved development velocity and product team confidence thanks to clear lineage and an accessible dashboard from Pachyderm.

Adarga

Stephen Bull

Data Science Manager