🤖 Primex Labs

Company Overview

Primex Labs is an AI-first fintech company that provides credit decisioning, fraud detection, and risk assessment services to 200+ financial institutions. Their platform processes 50 million decisions daily, powered by hundreds of machine learning models.

The Challenge

Primex's data science teams faced significant obstacles in scaling their ML operations:

• Feature engineering bottleneck — Data scientists spent 70% of their time on feature preparation
• Training-serving skew — Models performed differently in production than in training
• Limited observability — Couldn't detect model drift until business metrics degraded
• Governance gaps — Regulators required explainability that existing infrastructure couldn't provide

The Solution

Primex deployed Datorth's AI-ready data platform to build a world-class ML infrastructure:

Unified Feature Store

• Built centralized feature repository with 5,000+ production features
• Implemented point-in-time correct feature retrieval for training
• Deployed real-time feature serving with <5ms p99 latency
• Created feature marketplace for cross-team discovery and reuse

ML Model Telemetry

• Implemented comprehensive model monitoring across 500+ production models
• Built automated drift detection with configurable alerting thresholds
• Created A/B testing framework with statistical significance tracking
• Deployed model performance dashboards with business metric correlation

AI Governance Framework

• Automated model documentation and lineage tracking
• Built explainability pipelines for regulatory compliance
• Implemented bias detection and fairness monitoring
• Created approval workflows for model promotion to production

Results

Data Science Productivity

• 70% → 20% time spent on feature engineering
• 3× faster model development cycle
• 80% feature reuse rate across teams
• 50+ models/month deployment velocity (up from 5)

ML Operations Excellence

• <5ms p99 feature serving latency
• Zero training-serving skew incidents
• 15 minute mean-time-to-detection for model drift
• 100% model explainability for regulatory audits

Business Impact

• 23% improvement in credit decision accuracy
• $31M reduction in fraud losses for customers
• 40% faster regulatory approval for new models
• 5 new enterprise customers citing AI capabilities

Customer Testimonial

"Datorth transformed our ML infrastructure from a science project into an industrial-grade platform. Our data scientists now focus on model innovation instead of data plumbing, and we can prove to regulators exactly how our models work."

— Dr. James Park, VP of Machine Learning, Primex Labs

Technology Stack

• Datorth Feature Store with real-time and batch serving
• Datorth ML Observability for model monitoring
• Datorth Governance for AI compliance
• Integration with Databricks, MLflow, Kubernetes, and custom training infrastructure

ML Platform Capabilities

• Feature Engineering — Batch and streaming feature pipelines
• Feature Serving — Low-latency online inference
• Model Registry — Versioned model artifacts with metadata
• Model Monitoring — Drift detection, performance tracking
• Explainability — SHAP values, feature importance, decision traces

What's Next

Primex is expanding their Datorth deployment to support large language models (LLMs) for document processing and conversational AI, with a focus on retrieval-augmented generation (RAG) pipelines.