<aside> đ Sieve is the platform to discover, design, and run AI features at scale. AI development is moving away from being predominantly about training & finetuning, and more towards how people combine models together to make specific use cases work. Our platform is the best development experience built around this growing trend.
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Concretely, itâs still really difficult to find the right models for a specific use case, combine them with just the right logic & other models, and then deploy that pipeline at scale â especially for team just getting started with AI.
Discover
HuggingFace is amazing, but itâs pretty overwhelming for most people with little AI knowledge. Weird model names, many models that donât work, unintuitive demos, and maybe too many options to choose from. Also, not every model is on there and some of the most useful models for niche use cases are stored as messy GitHub repositories with weights on Google Drive.
Design
Once youâve found whatâs out there, youâll design a pipeline and see how it performs. Model code tends to be messy so you first need to âmake the code workâ with all the weird CUDA & package dependencies. And once you have managed to get things running, you spend a lot of time commenting / uncommenting parts of your code, running steps in isolation, storing intermediate outputs to debug a specific portion of your pipeline, swapping out specific models (like a face detector), writing custom visualization code, and then fixing your pipeline logic. This ends up being a tedious and cumbersome to go through.
Run
After youâre satisfied with your pipeline, you may choose to have others on your team try it. This may mean spinning up a quick UI for your team hosted on a GPU somewhere, which takes some unwanted effort. Once youâve got the internal pass, youâll then look to move this to a setup that scales in production â which means worrying about Kubernetes, CUDA drivers, autoscaling, observability, GPU utilization, large batch requests, retries, error handling, and more.
We think there is a better experience to be built around the three steps:
While we believe the core platform experience is the most valuable part of Sieve, it doesnât mean much unless we prove to people that the platform can easily solve use cases they care about.