data quality engine

DQE: AI-powered Quality Assurance

Our self-learning solution identifies errors and anomalies and provides an easy workflow to correct them. The DQE system learns from human inputs and becomes more accurate over time.

structured data statistical modeling / AI frameworks
machine learning models for anomaly detection
self-learning neural networks
see how much you can save using our free ROI calculator

Features: Identifying Errors and Facilitating Correction

Our DQE is a scalable platform with a customizable feature that enables each customer access clean data and run analytics for better decision making and profitability, such as predicting shipments in jeopardy

Has the ability to run through high volume and velocity data in real-time - the biggest challenge in Data Quality Measures

Uses a deep learning algorithm that learns to recognize anomalous patterns in data

Tailored to fit and improves customer data architecture to achieve accurate, clean and normalized data

Conducts a granular analysis of data inconsistencies and suggests automated data fixes for anomalous data

Benefits: Operational Efficiency and Major Cost Savings

Decreases human effort to clean data - approximately 20 minutes for each error

Improves planning & forecasting accuracy, which reduces capital expenditures and optimizes operations

Reduces backorder rate, increases on-time delivery

Optimizes delivery routes and increases on-time delivery

Increases on-time delivery

Get started with your data quality engine today