Flawd
Flawd is an AI-powered usability testing platform that runs autonomous AI personas on live products to identify UX issues before real users encounter them. Teams define goals in plain English, and AI users navigate, click, and interact naturally—providing session recordings, step-by-step screenshots, and post-test interviews. The platform offers a free tier and paid plans starting at $99 per month, with sessions as the only variable.
- Artificial Intelligence
- AI Agents
- Data & Analytics
- Software Only
Funding
Founders
Product
Problem
Traditional usability testing is slow and resource-intensive, requiring teams to recruit participants, schedule sessions, and synthesize findings—a process that often takes weeks. By the time results are ready, the feature being tested has usually already shipped or the next sprint has moved on, leaving UX issues undiscovered until real users encounter them.
Solution
Flawd provides an AI usability testing platform that runs autonomous AI personas on live products to uncover UX problems before real users hit them. Teams define personas with specific goals, patience levels, and technical comfort, then set tasks in plain English—such as "purchase a product and complete checkout." The AI users navigate the actual product independently, clicking, typing, scrolling, and reacting to what they see, making mistakes and getting frustrated just like real users. When issues arise, Flawd captures step-by-step screenshots, full session replays, and even conducts post-test interviews where the AI user explains what confused them and why. This approach delivers the qualitative depth of user interviews at the speed and scale of automated testing, without recruiting, scheduling, or no-shows.
Target Audience
Flawd is designed for product managers, designers, engineers, and QA leads who need to validate user flows before launch and catch UX issues alongside functional bugs. It serves teams that already run usability tests or know they should, offering a faster alternative to traditional methods.
Features
- Realistic AI personas with adjustable patience, attention, and technical comfort thresholds that approach interfaces differently
- Plain-English goal definition with success conditions, such as reaching a confirmation page or completing a form submission
- Post-test interviews with AI users that provide qualitative insights grounded in their actual experience, including pain points and emotional reactions
- Step-by-step screenshots, full session replays, and user thinking/observation logs showing exactly where and why users get stuck
- Goal success tracking with pass/fail rates, engagement trend analysis, and error tracking categorized by type, frequency, and impact severity
- Local testing capability via `npx flawd localhost:3000` for running tests against development environments
- Custom persona builder with demographics, OCEAN personality traits, values, behavior patterns, and trust/frustration triggers