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Overview

Quell offers AI-powered User Acceptance Testing (UAT) agents that help to automate the acceptance testing process, ensuring that software development meets acceptance criteria.

Quell AI agents are capable of testing acceptance criteria, debugging, and creating detailed tickets. These UAT AI Agents fit seamlessly into your workflow, working as integral team members for product managers and founders for efficient User Acceptance Testing.

This AI tool automatically checks builds against acceptance criteria which can be sourced from Linear tickets, Jira tickets or even Figma designs, and tests these against Vercel, Netflify, and other builds.

This helps improve the speed and reliability of build deployments using both automatic and manual AI UAT, proven UAT testing agents, and automated testing tools for a streamlined validation and delivery process.

The testing capabilities of Quell AI agents are powered by advanced AI and machine learning, providing AI-enhanced insights. The platform also features automated issue ticketing and build monitoring, offering real-time analytics to ensure correct build deployments.

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Initial release of Quell.

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Pros and Cons

Pros

Automated UAT testing

Debugging support

Detailed ticket creation

Seamless workflow integration

Acceptance criteria testing

Can source from Linear tickets

Can source from Jira tickets

Can source from Figma designs

Tests against Vercel builds

Tests against Netflify builds

Proven UAT testing agents

Automated testing tools

Automated issue ticketing

Real-time build monitoring

Integrated into existing workflow

Improves deployment speed

Improves deployment reliability

Real-time analytics

Supercharging founders and product managers

Accelerated build deployment

Optimized build testing

Automated build checking

Real-world user acceptance

Free first UAT agent

Integration with Github

Integration with Linear

Integration with Jira

Integration with Slack

Integration with Figma

Integration with Vercel

Integration with Netflify

Integration with GDrive

Machine learning capabilities

Auto testing of acceptance criteria

Transformation of testing capabilities

Peace of mind on deployments

Faster bug detection

Less deployment complexity

More deployment quality

Seamless issue spotting

Identification of critical bugs

Automated UAT for Vercel deployments

Optimized monitoring solutions

QA as a competitive advantage

Automated transition from testing to deployment

View 40 more pros

Cons

Limited tool integrations

Product-specific testing criteria

Dependent on ticket systems

Limited free trial

Requires setup

Deployment limited to Vercel, Netflify

Expensive Pro package

No custom testing options

Limited use cases

View 4 more cons

Q&A

What is Quell?

Quell is an AI-powered User Acceptance Testing (UAT) agent platform that helps automate the acceptance testing process. It uses advanced AI and machine learning to ensure software development meets defined acceptance criteria. Besides, Quell also automates issue ticketing and build monitoring, offering real-time analytics for correct build deployments.

How do Quell AI-powered UAT agents help in software development?

Quell's agents play a pivotal role in software development by automating the acceptance testing process, which ensures that the software meets the set acceptance criteria. They are capable of conducting acceptance tests, debugging, creating detailed tickets, and seamlessly fitting into your workflow. Moreover, they use AI and machine learning to enhance testing capabilities significantly.

How can acceptance criteria for UAT be sourced from Jira, Linear, or Figma designs?

Quell automatically checks the builds against acceptance criteria sourced from Linear tickets, Jira tickets, or even Figma designs. These sourced criteria guide how the AI agents perform UAT, focusing on the requirements stated in these tickets or designs.

How can Quell help improve the speed and reliability of build deployments?

Quell improves the speed and reliability of build deployments by automatically checking against the acceptance criteria. It accomplishes this through its advanced UAT testing agents and automated testing tools that validate the builds for deployment, thereby streamlining the validation and delivery process.

How does Quell integrate into a team's workflow?

Quell AI agents can be integrated seamlessly into a team's workflow. These agents work as vital team members for product managers and founders, making the User Acceptance Testing (UAT) more efficient. They are capable of performing tasks like testing acceptance criteria, debugging issues, and even creating detailed tickets.

What does it mean to do both automatic and manual AI UAT with Quell?

Automatic and manual AI UAT refers to the dual approach that Quell provides for conducting UAT. Automatic UAT means the AI agents automatically check builds against acceptance criteria and conducts testing. Manual UAT, on the other hand, allows users to manually guide the AI agents during the UAT process, providing more control and flexibility.

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How do Quell AI agents enhance testing with machine learning?

Quell employs machine learning to enhance its testing capabilities. The AI-enhanced insights provided by Quell are a result of the advanced AI and machine learning algorithms it uses. These algorithms empower Quell's AI agents to produce more accurate and insightful UAT results, thereby ensuring the right builds are deployed at the right time.

How does Quell handle issue ticketing and build monitoring?

Quell has automated issue ticketing and build monitoring. This allows the software to automatically create tickets for issues found in the build during User Acceptance Testing (UAT), reducing the need for manual issue logging. Its build monitoring feature keeps track of build deployments, providing real-time analytics to ensure correct deployments.

What type of real-time analytics do Quell offer?

Quell offers real-time analytics to enable users to monitor the status of their builds and keep track of any issues that arise. This feature serves to provide immediate insights into build deployments, thereby ensuring they are correctly deployed and any issues can be swiftly addressed.

What deployment platforms are compatible with Quell?

Quell is compatible with a range of deployment platforms including Vercel, Netflify, and more. This flexibility allows users to test their builds on various platforms, ensuring comprehensive and reliable User Acceptance Testing (UAT).

What notable capabilities do Quell testing agents have?

Quell's testing agents possess advanced capabilities powered by AI and machine learning. These include: automated UAT, debugging, ticket creation, build monitoring, and providing AI-enhanced insights. Furthermore, they can seamlessly work with other team members, thereby enhancing the effectiveness of the UAT process.

How does Quell facilitate feedback on test results?

Quell facilitates feedback on test results by automatically creating detailed tickets for issues found during the User Acceptance Testing (UAT). The tickets provide clear information about the issues, allowing the team to address them quickly and expediently.

How can I use Quell for my software validation process?

Quell can be used in your software validation process by automating the acceptance testing based on the defined criteria. This includes checking the builds against acceptance criteria, testing, debugging, and validating whether the build is ready for deployment or not. This leads to a streamlined validation and delivery process with improved speed and reliability.

What types of software development projects can Quell be used for?

Quell can be used for a variety of software development projects as it is designed to ensure that any software meets defined acceptance criteria. This encompasses projects across different development platforms and frameworks, including those that require automated testing for a streamlined validation and delivery process.

How does Quell improve the efficiency of the User Acceptance Testing (UAT) process?

Quell improves the efficiency of the User Acceptance Testing (UAT) process by automating the testing based on acceptance criteria. Its AI-powered UAT agents not only conduct acceptance tests and debugging but also create detailed tickets, thereby making the UAT process faster and more reliable.

How do debugging and ticket creation work in Quell?

In Quell, debugging and ticket creation are automated processes carried out by its AI-powered agents. The agents are capable of identifying bugs or issues during the UAT process and then automatically create detailed tickets for these issues. This saves developers time and ensures comprehensive documentation of any issue that arises during the testing phase.

Is Quell compatible with my existing tools like Github, Linear, Jira etc?

Yes, Quell is highly versatile and integrates seamlessly with existing tools such as Github, Linear, Jira, and others. This integration allows Quell's agents to leverage these platforms for sourcing acceptance criteria, enhancing the robustness and comprehensiveness of the UAT process.

Do Quell offer a free trial for users testing the platform?

Yes, Quell does offer a free trial for users who want to test the platform before commitment. The free trial experience allows firsthand use to understand how Quell agents can transform any team's UAT workflow and boost deployment velocity.

How quickly can I set up Quell?

Quell can be set up within minutes. The setup process involves connecting your issue tracker, repository, or deployment environment, choosing your testing preferences, and letting Quell's AI agents handle the rest.

What are Quell's pricing tiers and what features do they include?

Quell offers two pricing tiers: Pro and Enterprise. The Pro plan costs $300 per month and offers up to 100 tasks per month, suitable for individuals. The Enterprise plan costs $1500 per month, offering up to 1000 tasks per month and is designed for team collaboration and premium integrations.

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