Skene
Skene is a PLG iteration engine that automates onboarding tests, activation improvements, and retention loops.
Visit
About Skene
Skene is a fully automated PLG iteration engine that helps products grow without growth teams. Built for indie developers and early-stage startups, Skene handles continuous optimization of onboarding, activation, and retention — all based on understanding the customer code.
The platform observes user actions to detect friction and activation drop-off. It then automatically creates and tests improved versions of user flows, measures impact, and deploys the winning configuration. This means your onboarding improves itself, activation becomes smoother, and retention loops stay optimized over time.
Instead of dashboards full of knobs or weekly manual growth meetings, Skene offers a self-learning growth engine. Indie developers use it to offload growth work they don't have hours for. Startups use it as a “growth team in a box.” PLG companies use it to tighten activation and expand LTV without adding headcount.
The platform observes user actions to detect friction and activation drop-off. It then automatically creates and tests improved versions of user flows, measures impact, and deploys the winning configuration. This means your onboarding improves itself, activation becomes smoother, and retention loops stay optimized over time.
Instead of dashboards full of knobs or weekly manual growth meetings, Skene offers a self-learning growth engine. Indie developers use it to offload growth work they don't have hours for. Startups use it as a “growth team in a box.” PLG companies use it to tighten activation and expand LTV without adding headcount.
You may also like:
Sourcicle
Find candidates, automate outreach, and generate client-ready reports without tab-switching, LinkedIn scraping, or enterprise pricing.
Ai Watermark Remover
Advanced AI watermark remover that cleanly removes logos, text, and stamps from photos in seconds.
Reddit Post Summarizer
AI-powered Reddit summarizer Chrome extension—summarize threads, analyze subreddits, roast discussions, or explain simply.