The development of computer vision applications has been stuck in roughly the same workflow for years: collect data, annotate it, train models, write pipelines, then spend months - or often years - getting something useful into production, if ever.
We think that is about to change.
With Viso Now, you can give AI real images or video, describe what you want it to understand, and build a working vision app from there. It can reason about real-world scenes, activities and situations, and build a complete application with logic, live dashboards, API integration or notifications.
It feels much closer to building with an AI agent than building a traditional computer vision system.
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!