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Velaro — AI user behavior analytics
AI-powered heatmaps & insights that explain user behavior
Velaro is a lightweight alternative to bulky analytics tools like Hotjar or PostHog. It combines heatmaps, session recordings, funnels, and an AI assistant so you can ask questions like “Why are users dropping off on checkout?” and get direct, actionable answers. Instead of digging through dashboards, Velaro surfaces friction points, user behavior patterns, and practical ideas in a simple interface.
I recently started building Velaro after getting frustrated with traditional analytics tools that bury you in dashboards, graphs, and filters when all you really want to know is: “What are users actually doing, and what should I fix next?”
Velaro combines:
Heatmaps to see where people click, scroll, and focus
Session recordings to watch real user journeys
An AI assistant you can ask in plain language for insights and recommendations
The goal is to go from “I have data” to “I know what to change” in minutes, not hours.
This is an early-stage project and I’d love your help kicking the tires:
Try it on a real site and tell me where it breaks or feels rough
Share which insights you’d want the AI to surface first
Tell me any gaps you feel today’s analytics tools don’t solve
I’m using this launch as a feedback loop, so I’ll be iterating quickly based on your comments and use cases. 🚀
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About Velaro — AI user behavior analytics on Product Hunt
“AI-powered heatmaps & insights that explain user behavior”
Velaro — AI user behavior analytics was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #13 on the daily leaderboard. Velaro is a lightweight alternative to bulky analytics tools like Hotjar or PostHog. It combines heatmaps, session recordings, funnels, and an AI assistant so you can ask questions like “Why are users dropping off on checkout?” and get direct, actionable answers. Instead of digging through dashboards, Velaro surfaces friction points, user behavior patterns, and practical ideas in a simple interface.
Velaro — AI user behavior analytics was featured in Productivity (652.1k followers), Analytics (171.9k followers) and Artificial Intelligence (469k followers) on Product Hunt. Together, these topics include over 242.6k products, making this a competitive space to launch in.
Who hunted Velaro — AI user behavior analytics?
Velaro — AI user behavior analytics was hunted by Hector. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Velaro — AI user behavior analytics stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Hector
Hey Product Hunt 👋
I recently started building Velaro after getting frustrated with traditional analytics tools that bury you in dashboards, graphs, and filters when all you really want to know is: “What are users actually doing, and what should I fix next?”
Velaro combines:
Heatmaps to see where people click, scroll, and focus
Session recordings to watch real user journeys
An AI assistant you can ask in plain language for insights and recommendations
The goal is to go from “I have data” to “I know what to change” in minutes, not hours.
This is an early-stage project and I’d love your help kicking the tires:
Try it on a real site and tell me where it breaks or feels rough
Share which insights you’d want the AI to surface first
Tell me any gaps you feel today’s analytics tools don’t solve
I’m using this launch as a feedback loop, so I’ll be iterating quickly based on your comments and use cases. 🚀