Etiq provides a testing and monitoring tool for data pipelines and machine learning models, focusing on issues such as data drift, bias, and performance degradation. By automating the validation process, Etiq reduces debugging time and enhances the reliability of data-driven applications, allowing teams to focus on delivering value rather than troubleshooting errors.
Funding
$120K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Data scientists face challenges in maintaining the reliability and fairness of machine learning models due to issues like data drift, bias, and performance degradation. Building and debugging tests for these issues is complex and time-consuming, diverting resources from core value delivery.
Solution
Etiq provides a testing and monitoring tool for data pipelines and machine learning models, automating the validation process to ensure robust and fair pipelines in production. The software allows users to test and monitor models for data errors, data drift, target leakage, data bias, and drops in model performance. By proactively detecting potential errors and biases, Etiq reduces debugging time and enhances the reliability of data-driven applications. The platform offers configurable drift tests and monitors with out-of-the-box metrics, root cause analysis, and notebook templates to address fairness problems.
Target Audience
Etiq is designed for data scientists and machine learning engineers who need to ensure the robustness, fairness, and reliability of their data pipelines and models.
Features
- Automated tests for monitoring data pipelines for data errors
- Model performance validation before deployment and continuous monitoring post-deployment
- Configurable drift tests and monitors with multiple out-of-the-box metrics
- Built-in bias tests to mitigate unintentional discrimination in ML models
- Root cause analysis to identify and diagnose the source of problems
- Interactive dashboards and charts for visualizing pipeline insights
- Documented snapshots and scans in a config file
- Python package installation and one-click deployment on AWS Marketplace