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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Having the most skilled developers isn't enough if testing processes are hindering their progress; in fact, a staggering 80% of your software tests may be ineffective. The challenge lies in identifying which 80% is truly unnecessary. We utilize your data to pinpoint the essential 20%, enabling you to accelerate your release process. Our predictive test selection tool, inspired by machine learning techniques employed by leading companies like Facebook, is designed for easy adoption by any organization. We accommodate a variety of programming languages, test frameworks, and continuous integration systems—just integrate Git into your workflow. Launchable employs machine learning to evaluate your test failures alongside your source code, sidestepping traditional code syntax analysis. This flexibility allows Launchable to effortlessly extend its support to nearly any file-based programming language, ensuring it can adapt to various teams and projects with differing languages and tools. Currently, we provide out-of-the-box support for languages including Python, Ruby, Java, JavaScript, Go, C, and C++, with a commitment to continually expand our offerings as new languages emerge. In this way, we help organizations streamline their testing process and enhance overall efficiency.

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

Screenshots View All

Screenshots View All

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Android
Apple iOS
Azure Blob Storage
Bitbucket
DataRobot
GitHub
Google Cloud BigQuery
IBM watsonx.data
JUnit
Jenkins
Jest
Kubeflow
MLflow
Maven
NUnit
PyTorch
Snowflake
Travis CI

Integrations

Amazon SageMaker
Amazon Web Services (AWS)
Android
Apple iOS
Azure Blob Storage
Bitbucket
DataRobot
GitHub
Google Cloud BigQuery
IBM watsonx.data
JUnit
Jenkins
Jest
Kubeflow
MLflow
Maven
NUnit
PyTorch
Snowflake
Travis CI

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

Launchable

Country

United States

Website

www.launchableinc.com

Vendor Details

Company Name

Robust Intelligence

Founded

2019

Country

United States

Website

www.robustintelligence.com

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Software Testing

Automated Testing
Black-Box Testing
Dynamic Testing
Issue Tracking
Manual Testing
Quality Assurance Planning
Reporting / Analytics
Static Testing
Test Case Management
Variable Testing Methods
White-Box Testing

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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Alternatives

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