This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
OpenIngress checks whether AI agents can actually get around a live UI - public sites and internal tools - click the right things, find screens, and finish tasks instead of bouncing off broken nav, unlabeled buttons, or flows that only work for humans. We map what an agent can see and do, then report where navigation breaks.
we built OpenIngress after auditing live UIs for whether AI agents could actually use them - starting with ecommerce (product → cart → checkout), and the same failure pattern showed up on internal tools too: unlabeled controls, drawers, modal traps, state that only humans can see.
humans usually made it. agents often didn’t. the useful output was always the same: the job, where it broke, what to fix.
today we’re open-sourcing the engine for live sites. paste a URL, crawl, explore, get coverage + break points.
findable ≠ usable. if agents are going to browse for people, you’ll want those failure points before the traffic shows up.
self-host it, try your site, tell us what breaks. for custom journeys / authenticated / internal tools, reach out!
The "what breaks" framing in the report output is genuinely smart, way more useful than a generic pass/fail score. Nice to see something built for agent traffic that doesn't just slap a chat box on a crawler.
A dashboard view comparing scores across multiple test runs would be huge, so you can see if a recent deploy made the site more or less navigable for agents. Right now it sounds like each audit is a standalone report, but tracking that trend over time is what teams would actually act on.
Would love to see an option to replay a failed agent session step by step and see exactly which click or page tripped it up, makes the report way easier to act on.
One thing that would help us a lot is letting us upload a customer journey script and then comparing how different agents perform on that exact path side by side. Right now the tasks feel generic so we have to handcraft each test, which gets tedious when we want to validate changes after every deploy.
About OpenIngress on Product Hunt
“Can AI agents use your UI?”
OpenIngress was submitted on Product Hunt and earned 11 upvotes and 9 comments, placing #71 on the daily leaderboard. OpenIngress checks whether AI agents can actually get around a live UI - public sites and internal tools - click the right things, find screens, and finish tasks instead of bouncing off broken nav, unlabeled buttons, or flows that only work for humans. We map what an agent can see and do, then report where navigation breaks.
OpenIngress was featured in Website Builder (9.6k followers), Artificial Intelligence (474.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 136.3k products, making this a competitive space to launch in.
Who hunted OpenIngress?
OpenIngress was hunted by Manu Pareek. 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 OpenIngress stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Manu Pareek
hey Product Hunt 👋
we built OpenIngress after auditing live UIs for whether AI agents could actually use them - starting with ecommerce (product → cart → checkout), and the same failure pattern showed up on internal tools too: unlabeled controls, drawers, modal traps, state that only humans can see.
humans usually made it. agents often didn’t. the useful output was always the same: the job, where it broke, what to fix.
today we’re open-sourcing the engine for live sites. paste a URL, crawl, explore, get coverage + break points.
findable ≠ usable. if agents are going to browse for people, you’ll want those failure points before the traffic shows up.
self-host it, try your site, tell us what breaks. for custom journeys / authenticated / internal tools, reach out!