Pleras uses AI to scan a website’s structure, copy, and user flow, automatically generating and ranking A/B test hypotheses. It then delivers production‑ready experiment code for platforms like Optimizely, VWO, LaunchDarkly, or custom JavaScript, letting growth, design, and engineering teams launch tests within hours.
Funding
Funding not disclosed
Founders
Product
Problem
Growth, design, and engineering teams often struggle to generate and implement high‑impact A/B test ideas quickly because creating hypotheses, writing experiment code, and integrating with testing platforms requires significant time and coordination.
Solution
Pleras applies AI to analyze a website’s structure, copy, and user flow, automatically generating ranked experiment hypotheses based on six scoring criteria. Users select a hypothesis, and Pleras produces deploy‑ready code compatible with Optimizely, VWO, LaunchDarkly, or plain JavaScript, tailored to the site’s design. The platform can ingest past experiment data to improve future suggestions, enabling teams to move from idea to live test within hours instead of weeks. By streamlining hypothesis generation, scoring, and code delivery, Pleras reduces the resource burden on growth, design, and engineering teams, allowing them to run more experiments and iterate faster.
Target Audience
Primary customers are growth teams, product designers, and front‑end engineers at SaaS and e‑commerce companies who run frequent A/B tests and need to accelerate the test creation workflow.
Features
- AI-driven analysis of page structure, copy, layout, and user flow to surface high‑value testing opportunities
- Automated ranking of experiment ideas on six criteria to prioritize the strongest hypotheses
- One‑click generation of production‑ready experiment code for Optimizely, VWO, LaunchDarkly, or custom JavaScript
- Ability to import historical experiment results, allowing the model to refine suggestions over time
- Built‑in security and quality checks (XSS, execution safety, visual validation) before code delivery
- Documentation and developer guides covering selectors, SPA handling, and platform integration details