Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The Failure Reporting, Analysis, and Corrective Action System (FRACAS) serves as a comprehensive feedback mechanism that facilitates collaboration between users and suppliers to gather, document, and evaluate failures related to both hardware and software systems. During the design evolution phase, corrective actions (CAR) are most effective, but as the design solidifies, implementing these actions becomes increasingly costly and constrained. The analysis conducted within this framework pinpoints necessary corrective measures that must be executed and verified to avert the recurrence of failures. By fostering reliability enhancements throughout the equipment's lifecycle, FRACAS can be applied during various testing phases, including in-house laboratory evaluations, field tests (whether alpha or beta), and production operations, enabling stakeholders to identify and address areas of concentrated issues within the equipment's design. This systematic approach not only enhances product reliability but also ensures a more efficient path to problem resolution.
Description
The Robust Intelligence Platform is designed to integrate effortlessly into your machine learning lifecycle, thereby mitigating the risk of model failures. It identifies vulnerabilities within your model, blocks erroneous data from infiltrating your AI system, and uncovers statistical issues such as data drift. Central to our testing methodology is a singular test that assesses the resilience of your model against specific types of production failures. Stress Testing performs hundreds of these evaluations to gauge the readiness of the model for production deployment. The insights gained from these tests enable the automatic configuration of a tailored AI Firewall, which safeguards the model from particular failure risks that it may face. Additionally, Continuous Testing operates during production to execute these tests, offering automated root cause analysis that is driven by the underlying factors of any test failure. By utilizing all three components of the Robust Intelligence Platform in tandem, you can maintain the integrity of your machine learning processes, ensuring optimal performance and reliability. This holistic approach not only enhances model robustness but also fosters a proactive stance in managing potential issues before they escalate.
API Access
Has API
API Access
Has API
Integrations
Amazon Redshift
Amazon S3
Amazon SageMaker
Azure Blob Storage
DataRobot
Databricks
Google Cloud BigQuery
Google Cloud Storage
H2O.ai
IBM watsonx.data
Integrations
Amazon Redshift
Amazon S3
Amazon SageMaker
Azure Blob Storage
DataRobot
Databricks
Google Cloud BigQuery
Google Cloud Storage
H2O.ai
IBM watsonx.data
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Qsoft
Website
www.qsoft.cc/qsoft_website/FRACAS.aspx
Vendor Details
Company Name
Robust Intelligence
Founded
2019
Country
United States
Website
www.robustintelligence.com
Product Features
CAPA
Audit Management
CAPA Planning
Change Management
Complaint Management
Incident Management
Nonconformance Tracking
Quality Control
Risk Management
Root Cause Analysis
Training Management
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization