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What is Launchable?
Having a team of highly skilled developers is not sufficient if the testing methodologies are obstructing their workflow; in fact, around 80% of software tests may prove to be ineffective. The real challenge is determining which 80% of those tests can be deemed unnecessary. By leveraging your data, we can identify the crucial 20%, thereby speeding up your release cycles. Our predictive test selection tool is influenced by machine learning strategies used by industry leaders such as Facebook, making it accessible for organizations of all sizes. We support a wide array of programming languages, testing frameworks, and continuous integration systems—simply integrate Git into your existing workflow. Launchable harnesses machine learning to analyze your test failures in conjunction with your source code, avoiding the pitfalls of conventional code syntax evaluation. This adaptability allows Launchable to seamlessly extend its compatibility to almost any file-based programming language, catering to diverse teams and projects that utilize various languages and tools. At present, we offer immediate support for languages such as Python, Ruby, Java, JavaScript, Go, C, and C++, while also pledging to continually broaden our language support as new ones emerge. By streamlining the testing process, we empower organizations to significantly boost their overall efficiency and focus on what truly matters—their core development goals. Ultimately, our approach not only optimizes testing but also enhances the productivity of development teams.
What is FeedStock Cortex?
Cortex leverages advanced machine learning capabilities to seamlessly oversee research engagements and identify research incentives across various communication platforms. Our service offers the most streamlined and discreet research payment validation, ensuring that your organization remains compliant and functionally effective while relying on precise data for strategic decision-making. Functioning in real-time, Cortex automatically collects, analyzes, and securely understands all research interactions, both internal and external, within your organization's information flow. This groundbreaking system alleviates the burden of monitoring these interactions internally and eliminates the need to rely on and reconcile sell-side data, enabling your investment professionals to focus on their primary areas of expertise. Ultimately, Cortex enhances your team's operational efficiency and effectiveness, fundamentally changing the way research interactions are handled. By integrating Cortex into your processes, you can expect a significant improvement in collaboration and insight generation across your organization.
Integrations Supported
Amazon Web Services (AWS)
Android
Apple iOS
Bitbucket
Cucumber
Cypress
GitHub
GitLab
Gradle
JUnit
Integrations Supported
Amazon Web Services (AWS)
Android
Apple iOS
Bitbucket
Cucumber
Cypress
GitHub
GitLab
Gradle
JUnit
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Launchable
Company Location
United States
Company Website
www.launchableinc.com
Company Facts
Organization Name
FeedStock
Date Founded
2015
Company Location
United Kingdom
Company Website
feedstock.com/products/cortex/
Categories and 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
Categories and Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization