Product Positioning & Context
Nimbia is an AI that does screen-sharing calls to onboard and train new users of software products. It speaks, listens, and can actually click on the user's screen, so it can be truly helpful. The very first company using Nimbia is growing 40% faster because of it. When they ran an A/B test against their previous onboarding solution, Nimbia delivered 1.4X higher week-one activation and trial-to-paid conversion rates.
Related Ecosystem & Alternatives
Discover adjacent products, open-source repositories, and developer tools sharing similar technical architecture.
Deep-Dive FAQs
What is Nimbia?
Nimbia is a digital product or tool described as: AI screen-sharing calls for user onboarding
Where did Nimbia originate?
Data for Nimbia was aggregated directly from the Product Hunt community ecosystem, representing raw developer and early-adopter sentiment.
When was Nimbia publicly launched?
The initial public indexing or launch date for Nimbia within our tracked developer communities was recorded on August 25, 2026.
How popular is Nimbia?
Nimbia has achieved measurable traction, logging over 156 traction score and facilitating 50 recorded discussions or engagements.
Which technical categories define Nimbia?
Based on metadata extraction, Nimbia is categorized under topics such as: Customer Success, SaaS, Artificial Intelligence.
Are there open-source alternatives related to Nimbia?
Yes, the GitHub ecosystem contains correlated projects. For example, a repository named nikmcfly/MiroFish-Offline shares highly similar architectural descriptions and topics.
How does the creator describe Nimbia?
The original author or development team describes the product as follows: "Nimbia is an AI that does screen-sharing calls to onboard and train new users of software products. It speaks, listens, and can actually click on the user's screen, so it can be truly helpful. The ..."
Community Voice & Feedback
Joris 💪 Super cool product, man!
That screenshot experiment was two years ago, and it still took your team eighteen months to make it reliable enough to put in front of real users. Congrats on getting it out the door.
Tested a very first version of the product which was already amazing! Excited to see where thinks going
Brilliant stuff. Everything coming from @machielse is something I keep an eye on, and this one really grabbed my attention. Works just great. Can't emphasize this enough. It's amazing how something that's so complex under the hood works so elegantly and smoothly.
Lekker Joris, congrats! Been giving screenshare demos for Salonized myself for years so I get exactly why you built this. Good luck with the launch.
I've given so many product demos over screenshare to small contractors, always walking the customer through it themselves while I explained stuff live. Obviously it converted way better than without, but it ate up a lot of my time.At the same time, I valued the personal contact. Those calls gave me a ton of feedback on the product itself: hearing what people actually get stuck on, the words they use for their problem, stuff you'd never get from a support ticket.Nimbia takes that call off your plate, which is great. Curious though how you're handling that feedback loop. When the AI runs the call instead of me, how do I still get that "oh interesting, they always struggle here" insight? Feels like that's the hardest part to replace.
Hi Product Hunt! 👋Maker here. Some backstory on why this exists.My first B2B company was a lead gen product, where I personally onboarded every single customer 1-on-1. My next product was in user onboarding itself (demo videos, similar to Supademo). So I’ve spent years inside this problem: those calls work, but they don’t scale, so most users never get one.About two years ago, right when GPT-4o came out, I ran an experiment. I gave it a goal inside our app plus a screenshot, and asked for the next step. I performed that step myself, sent it the new screenshot, and asked again. It walked through the entire flow on the first attempt. I hadn’t expected that at all, and it took me a while to realize what it meant: someone was going to use this to replicate those 1-on-1 calls, and that would obliterate the legacy approach of product tours, help docs and tooltip overlays. I figured that someone should be me.Going from that experiment to an AI that reliably does live screen-sharing calls with real users turned out to be very hard. It took our team 18 months. But it works now: it talks with your users like a human CS agent would, it sees their screen and clicks on things for them, and you add it to your app with a single line of JavaScript. We train it on your product, even on recordings of your past onboarding calls.The first company running it is growing 40% faster.Happy to answer anything about how we built this, what broke along the way, or where it's going.
I often send Google Docs with instructions and screenshots, this is the ideal replacement!
Congrats on the launch @machielse. The product looks really helpful and really like the website design.
Wow... this is solving each CS / onboarding painpoint i've ever had in the past. Looks like Nimbia is onto something, awesome to see!
seems like a super interesting product solving a real pain point. onboarding customers at scale is hard!!
Love this. Product tours were always a poor stand-in for someone sitting next to you, and you're basically putting that person back. Congrats on shipping it, Joris!
Great timing for launching this. Its exactly what we have been looking for. I just signed up and eager to see the demo.
Congrats Joris. Most onboarding tools optimize the top of the funnel. Going after the users who'd normally get a link is the harder and more valuable half.
This is going to help a lot to improve new user conversion rates to paid! Can you have complete free-form conversations with the AI? How are you preventing prompt-injections from screen content?
Discovery Source
Product Hunt Aggregated via automated community intelligence tracking.
Tech Stack Dependencies
No direct open-source NPM package mentions detected in the product documentation.
Media Tractions & Mentions
No mainstream media stories specifically mentioning this product name have been intercepted yet.
Deep Research & Science
No direct peer-reviewed scientific literature matched with this product's architecture.
SaaS Metrics