Your machine learning stack is not complete without All Vision. Our tool finds and tracks new data patterns for you and is built for your existing ML stack.
Find patterns in data with no code
Your machine learning stack is not complete without All Vision. Our tool finds and tracks new data patterns for you and is built for your existing ML stack.
Hello PH community! I’m Katie 👋 the first hire and product lead at All Vision Tech. I’m exited to announce our company’s commercial debut. A year ago, our data science team brainstormed and delivered a solution for the US Space Force. We learned how powerful (and underused) unsupervised learning is, and thought about how it could have solved past problems we’d faced at work. The problem we’re solving: Supervised ML has major blindspots when it comes to dealing with a changing world. We help beca
Thanks for Hunting this @katie_kuzin , If anyone is interested in looking at how we are upgrading unsupervised learning under the hood feel free to check out our technical white paper at : https://b25c15fa-312b-4cd5-915b-fbe99ba66fbf.filesusr.com/ugd/87927b_34940f491f6441fc99413f5795b72f94.pdf
Thanks @katie_kuzin !! We've come a long way as a team to get here, and as a cofounder I'm excited to engage with the PH community. Looking forward to meeting the folks who sign up here: https://app.all.vision/signup#loaded
Very interesting product--data integrity always seems to be the crux, so solving for patterns with partially or imperfectly labeled data addresses a major pain point. Very cool!
I can see use for this in the growing remote patient monitoring field as healthcare organizations create home-grown products and implement pre-made products to see changes in patient metrics. Especially important to have a tool like this that doesn't require access to "protected" data (HIPAA). Exciting work!
The scores reflect launch-period engagement. Historical data is preserved and doesn't change retroactively. The build date at the bottom shows when the index was last refreshed.
Check the similar products section on this page, or browse the category pages linked in the tags above. Each category page shows all products for a given year, sorted by engagement.
A measure of community engagement at launch. Higher means more people noticed and interacted with the product. It's a traction signal, not a quality rating.
Discussion threads divided by interest score. Above 0.30 is strong. Below 0.15 suggests the product got clicks but not conversation.