Viso Now is a self-building AI vision platform that turns images, video, and camera feeds into working computer vision applications. Describe what you want to understand, and Viso Now builds the agentic vision logic and custom live dashboards. All without model training, annotation, or writing code.
Hey everyone 👋 I'm Talia, member of the viso.ai team!
So, why Viso Now. As we've been in the computer vision space for quite some time, we saw that our customers kept running into the same annoying gap on their projects: the model does its job and flags something, but then what? In practice, that "then what" turns into someone hacking together a script to dump detections somewhere, a human squinting at a spreadsheet, and alerts that either don't exist or exist in someone's inbox filter that nobody trusts. We got tired of rebuilding that glue every time, so we built it once, properly.
What that looks like in practice: you point Viso Now at your footage or images, it routes anything flagged into a review queue that's actually built for a person to move through quickly (not a data scientist, an actual ops or QA person), and it pings you the moment something crosses whatever threshold matters to you.
The part I like most is that it doesn't care what your "something" is. We've had early users piloting it for things as different as catching defects on a production line and, genuinely one of my favorite examples, a small marine biology team using it to track coral bleaching across reef survey footage. Same review-and-alert loop underneath, wildly different Tuesday for the person using it.
If you're running or experimenting with a CV model and have hit that same "okay but who actually looks at this" wall, I'd love to hear about it. Drop a comment, and I'll be in touch today!
Hello everyone, I'm LeePing, a Senior AI Engineering Lead at viso.ai and I build and deliver solutions for customers.
In the past, a large part of this involves collecting data, annotating them, training models, and repeating the process to improve models over time. There are some major disadvantages to this "traditional" approach - it's very time consuming and delays model deployment, the number of use cases it can tackle is limited, and effort is needed over time to continuously refine and improve the model.
With Viso Now, a lot of these pain points and limitations are taken away - I can work on many more solutions for customers in the same period of time! Kudos to the team for a great product 🚀 and looking forward to solving more problems with Viso Now!
What does it mean when it says 'building vision logic'? Is it combining pre-built models, or is it something else? Btw, Congratulation's @taliambender & team @Viso Now . 🚀🎊
Hi everyone, I'm Nico, viso.ai Co-founder. Most of what we have built at viso.ai has been for teams running live cameras in production, but the conversation I kept having was with people nowhere near that stage. They already had footage sitting on a drive somewhere, and they wanted to know what was in it without committing to a full ML project to find out.
Viso Now is the short route to that. You connect your video source, tell it what to look for, and you have something usable in the same sitting. Nothing to label, no model to train, no deployment.
I'm proud of my team for building this incredible tool, as I've been pushing for this one internally for a while. Curious what people point it at and welcome your comments and feedback.
I’ve had the privilege of watching this product change the way computer vision applications are built, making it possible to go from an idea to a working application in minutes. Organisations that may never have had the time, budget, or expertise to utilise the power of computer vision now have the ability to build and go live in one afternoon.
I’m incredibly excited about what we’re launching, the team behind it, the amazing community already forming around Viso Now, and what comes next.
Viso Now is IT!!!
Hey Product Hunt! Katie here 👋 I've watched @Viso Now go from a whiteboard idea to launching today
I speak with prospects and clients everyday, usually explaining computer vision rather than building it. Coming from an economics background, no ML experience, I still put together a defect detection setup and a logistics truck turnaround monitor, just by describing what I wanted to track 👀
What's stuck with me most is how fast the gap closes between "I have an idea" and "I have something working." That's usually the hardest, slowest part. Viso Now compresses it into minutes
Proud to be part of the team bringing this out today 💙
Hi everyone!! Yehjin here from the GTM team at viso.ai 👋 Sooo so excited to finally see Viso Now live on Product Hunt!
Viso Now makes getting started with computer vision so much easier. You can upload a video, type what you want to detect, and have a working vision application within minutes. No datasets to prepare or hundreds of images to annotate first.
Working at viso.ai and seeing how much work has gone into building this makes this launch feel extra special.
We’re all really proud of what we’ve built and even more excited to see people actually using it.
If you give Viso Now a try, let us know what you build! 🚀
As CTO, this launch is especially meaningful to me because Viso Now changes something fundamental about how computer vision software gets built.
For years, the hard part of computer vision was the model. Turning a camera feed into a useful application meant model selection, dataset generation and model training pipelines all of which require time and technical experitse - often before you can validate whether the requirements of the use case can be sufficiently met.
The hard part now is everything around the model: routing observations into a workflow a human can actually act on, reviewing outcomes at speed, setting thresholds that mean somethings and visualising the results for the business.
With Viso Now, we wanted to invert the workflow: start with the problem you want to solve in the physical world, describe it, and let the system build the vision logic around it. You can connect cameras, iterate on the behavior, and get to a working application dramatically faster.
But this ins't all value truly lands when someone can act on it. Viso Now automatically turns that logic into live dashboards: detections become charts, trends, and metrics that speak the language of the business. And through connectors, relevant outputs are sent straight into the tools your team already use.
Under the hood, making something feel this simple required solving a lot of hard engineering problems around vision reasoning, video processing, orchestration, and turning ambiguous natural-language intent into reliable application logic.
That’s been the fun part for our engineering team!
We’re still early, and I’d love feedback from builders here - especially on the kinds of real-world problems you wish to solve and the challenges you face.
Happy to answer any questions about the product or where we’re taking it next. 🚀
Making computer vision more accessible is exciting. Doing it while building a second product at our stage is the harder part.
That’s what makes Viso Now meaningful to me. It lowers the barrier for others to experiment with computer vision, while also representing a pretty significant step for us as a Seed-stage company.
Traditional computer vision often depends on specialist talent, complex infrastructure, and a lot of upfront investment just to get an idea off the ground. Those same constraints show up inside a startup too, with limited resources, constant prioritisation, and the challenge of deciding where every dollar of investment should go.
Working across finance and operations at viso.ai, I see those trade-offs first-hand. Proud of the team 🚀
Been an exciting journey building @Viso Now from the frontend side.
Seeing everything come together into a platform that makes computer vision more accessible and actually useful has been really rewarding.
A lot of thought, iteration, and teamwork has gone into this.
Really proud of what the team has built.
Hi everyone! 👋 I’m Hammas, the backend developer at viso.ai
Viso Now makes building real-world computer vision applications as simple as chatting with AI. You describe what you want to build, add supporting images or videos if needed, and the platform generates the application and dashboard for you.
Whether it’s factory safety monitoring, event detection, or another CV use case, what traditionally takes months can now be built and refined in hours.
You can also chat with your application to customise dashboards exactly to your needs, generate custom reports, and schedule those reports to be delivered at defined intervals — all without needing to build it yourself.
We also connect to cloud providers to automatically fetch and process data, and can send results to platforms like Slack, Teams, email and more.
We’re constantly working to make Viso Now more powerful, efficient and easier to use. 🚀
Really excited to see what everyone builds with it!
Can I connect viso now to other agents?? or how does the output integrations works? Looks great btw ❤️❤️
Hey Product Hunt! Daniela here from the Go-to-Market team at viso.ai 👋
I’ve been at viso.ai for a year now, and seeing Viso Now come to life has been incredible. It genuinely feels like we’re witnessing a huge shift in how people can use computer vision.
A big part of my role is hosting events, building communities and getting Viso Now in front of people. My favorite part is seeing their reaction when they try it for the first time. The idea that you can analyze and understand the physical world simply by writing a prompt still gets a lot of “wait... that’s it?” reactions. 🤯
Viso Now has become a real showstopper at our events, especially within the ML and AI communities in London and Milan.
Very proud to be part of the team bringing this to the world. 🚀
Hi Product Hunt!
The very first company we showed Viso Now to was a prospect we'd initially only been able to offer a traditional computer vision solution to. That would have meant months of development and $30,000 in investment before they even had real data, and the question they needed answered was simple: how do people actually interact with our new machine? It runs on its own, so do people still try to engage with it? Do they stand around watching, or just walk away and let it do its thing?
Two weeks later we gave them pre-beta access to Viso Now. They solved it in minutes, then kept refining the logic themselves. Now they have a fully shipped solution that took them hours to perfect, and instead of manually reviewing footage clip by clip, they get the answer through charts and dashboards.
Their first reaction was to call it "magic." We actually had to cut that line from our slides because it sounded too much like marketing copy. But it's genuinely how it felt to watch.
Don't take our word for it. Try Viso Now today, it's free.
Really interesting. Can I integrate cctv cameras to viso now? Getting data from the physical world sounds good
About Viso Now on Product Hunt
“Build computer vision applications with AI”
Viso Now launched on Product Hunt on September 10th, 2026 and earned 103 upvotes and 21 comments, placing #12 on the daily leaderboard. Viso Now is a self-building AI vision platform that turns images, video, and camera feeds into working computer vision applications. Describe what you want to understand, and Viso Now builds the agentic vision logic and custom live dashboards. All without model training, annotation, or writing code.
Viso Now was featured in Artificial Intelligence (478.9k followers), No-Code (6k followers) and Vibe coding (672 followers) on Product Hunt. Together, these topics include over 129k products, making this a competitive space to launch in.
Who hunted Viso Now?
Viso Now was hunted by Ben Lang. 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 Viso Now stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Ben Lang
Hey everyone 👋 I'm Talia, member of the viso.ai team!
So, why Viso Now. As we've been in the computer vision space for quite some time, we saw that our customers kept running into the same annoying gap on their projects: the model does its job and flags something, but then what? In practice, that "then what" turns into someone hacking together a script to dump detections somewhere, a human squinting at a spreadsheet, and alerts that either don't exist or exist in someone's inbox filter that nobody trusts. We got tired of rebuilding that glue every time, so we built it once, properly.
What that looks like in practice: you point Viso Now at your footage or images, it routes anything flagged into a review queue that's actually built for a person to move through quickly (not a data scientist, an actual ops or QA person), and it pings you the moment something crosses whatever threshold matters to you.
The part I like most is that it doesn't care what your "something" is. We've had early users piloting it for things as different as catching defects on a production line and, genuinely one of my favorite examples, a small marine biology team using it to track coral bleaching across reef survey footage. Same review-and-alert loop underneath, wildly different Tuesday for the person using it.
If you're running or experimenting with a CV model and have hit that same "okay but who actually looks at this" wall, I'd love to hear about it. Drop a comment, and I'll be in touch today!