Product Introduction

1. Quell's UAT AI Agent Platform is an automated acceptance testing solution that creates AI agents to validate software builds against predefined acceptance criteria from tools like Linear, Jira, or Figma. It detects critical bugs, flags issues, and generates tickets directly in integrated workflows, ensuring deployments on platforms like Vercel or Netlify meet quality standards. The platform eliminates manual testing bottlenecks by acting as an autonomous QA team member.
2. The core value lies in accelerating deployment cycles while maintaining quality, reducing human effort by 50% or more through AI-driven validation. It ensures builds align with product requirements by dynamically testing against real-time design updates, ticket status changes, and deployment triggers, enabling teams to ship faster with confidence.

Main Features

1. Automated acceptance criteria validation: Quell AI Agents test builds against criteria extracted from Linear tickets, Jira issues, or Figma design annotations. They simulate user interactions, check UI elements, and verify functionality, flagging discrepancies like missing CTA buttons or layout mismatches.
2. Cross-tool integration: The platform connects with GitHub, Vercel, Netlify, Slack, Figma, Jira, and Linear to monitor build deployments, track ticket statuses, and retrieve design files. Agents automatically trigger tests when deployments occur or tickets move to "Ready for QA" states.
3. AI-powered issue resolution: Detected bugs generate detailed Linear or Jira tickets with screenshots, console logs, and reproduction steps. The system prioritizes critical issues using machine learning models trained on historical deployment data, reducing false positives by 30%.

Problems Solved

1. Manual UAT inefficiency: Traditional user acceptance testing requires repetitive checks across tools, causing delays and human error. Quell automates 80% of validation tasks, cutting testing time from hours to minutes per build.
2. Target users: Founders, product leaders, and engineering teams at high-growth tech companies deploying frequent updates via Vercel or Netlify. It particularly benefits teams using Linear/Jira for task management and Figma for design collaboration.
3. Use cases: Testing a Netlify build against Figma design version 1.7 while cross-referencing Linear ticket "Add CTA Button," or validating a Vercel deployment against Jira acceptance criteria for a checkout flow.

Unique Advantages

1. Multi-source criteria aggregation: Unlike single-tool testing solutions, Quell combines acceptance criteria from design files (Figma), task tickets (Linear/Jira), and versioned code (GitHub) into unified test scenarios.
2. Context-aware AI agents: Agents understand design-to-code relationships, detecting subtle issues like padding mismatches between Figma specs and rendered components that static analyzers miss.
3. Deployment risk reduction: Proven to catch 92% of pre-production bugs, the platform reduces rollback incidents by 60% through real-time build monitoring and regression testing for every deployment.

Frequently Asked Questions (FAQ)

1. How does Quell automate UAT testing? Quell integrates with GitHub, Linear, Jira, Figma, Vercel, and Netlify to automatically trigger tests when builds deploy or tickets update. Agents extract acceptance criteria from connected tools, execute browser-based tests, and validate UI/functionality against specifications.
2. Do Quell Agents integrate with existing tools? Yes, the platform supports direct integrations with Linear, Jira, GitHub, Figma, Slack, Vercel, Netlify, and Google Drive. Agents use API connections to pull requirements, monitor deployments, and create tickets without manual data entry.
3. How quickly can I set up Quell? Setup takes under 10 minutes: connect your GitHub/Vercel/Netlify account, authorize Linear/Jira/Figma access, and define testing rules. Preconfigured templates for common workflows like "Figma-to-Vercel validation" enable immediate use.