Quell ✓

AI agents that supercharge UAT and catch critical bugs faster.

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Verdict

A quick read before you dig into the full page.

Best if

AI agents that supercharge UAT and catch critical bugs faster

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Expensive Pro package

Pick this when

Automated UAT testing

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.

Access & connections

Where you can use Quell, and what it plugs into.

Platforms

Web

Capabilities

What this tool accepts, produces, and is strongest at.

Input

Output

Supported features

QA Automation

Pros & 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

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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

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

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Limited use cases

FAQ 12

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.

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.

Quell ✓

Verdict

Overview

Best for

AI agents that supercharge UAT and catch critical bugs faster.

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