Here s a test I d run in MANTIS. I d start with two fresh browser sessions, record the same page in each, and click Reject all in one and Accept all in the other. Then I d repeat the same action, like opening a product page, and Compare the captures.
If a GA4 request appeared after Reject all, I d open it in the request tree and check three things: what triggered it, what data it sent, and what consent state MANTIS observed when it fired. I d also check whether the browser stored or sent an analytics cookie. The request alone wouldn t tell me whether the choice was respected. The payload, cookies, and timing would give me a clearer picture.
What s the first thing you check after Reject all ? What would make you dig deeper?
Hi Product Hunt, I'm Stéphane Hamel, creator of MANTIS.
When I created WASP in 2009, I wanted to go a step further. I wanted to see what a website was sending, who received it, and what triggered each request. The tool I had in mind was out of reach back then. OpenAI made it possible for me to finally build it.
I've spent years helping organizations understand their analytics and marketing technology. One question keeps coming back: what is this website actually sending, to whom, and why?
I built MANTIS to make that investigation easier. It captures browser activity, traces requests back to their initiators, and helps identify the tools and vendors behind them. You can inspect cookies and dataLayer events, compare consent scenarios, and turn findings into audit reports.
Capture evidence stays in your browser. Managed enrichment uses scrubbed request signatures to help identify unfamiliar technologies. Observations and AI-assisted findings still need human review.
MANTIS is in beta, and I'm looking for feedback from analysts, developers, and privacy practitioners. Which part of a tracking or consent audit takes you the most time, and what evidence would make it easier?
Congrats Stéphane! MANTIS looks like an incredibly powerful tool for audits. I definitely remember the WASP inspector, and this looks like a more than worthy successor to it.
Thanks @jason_packer !
When I created WASP, I had a vision of what I wanted it to be, but the technology was simply not available and pushing further was getting too expensive. Years later, and with the help of AI, I'm able to push the envelope and create a tool that is easy to use, visually appealing, and where results are self-explanatory.