GPU inference is 80% of the cost of running image search in production See What It Costs to Search 1M Images in Production: vecstore.app/blog/what-it-co…

i priced out every piece of running image search on 1M images. GPU inference, vector storage, S3, CDN, backend servers. the total came to $740/month for moderate traffic and $1,845/month at enterprise scale full breakdown: vecstore.app/blog/what-it-co…

fun use case we keep seeing: event photographers letting guests upload a selfie to find all their photos from the event. beats scrolling through 2000 pictures

here's what our image database can do: text to image image to image text in image face search product matching scene search logo detection none of these are separate features. they all work out of the box because the search understands the actual content of your images

the best part about Angular? you open a project from 3 years ago and it still makes sense

Add image search to your app without building it from scratch Try the demo vecstore.app

“We replaced both Pinecone and RDS with Neon, and latency dropped from 200ms to 80ms with a much simpler setup" Turns out, Postgres pgvector was all that they needed: neon.com/blog/vecstore-repla…