For academics and hobbyists getting started with a ML project

1 user
Public projects with unlimited viewers
Up to 10,000 labeled frames
Community Slack support


$1250 / month

For small teams improving a few ML models in production

Up to 5 users
Private projects with permissions
Default embedding models / user custom embedding upload
100k labeled frames + $1250 / mo per additional 100k
200k unlabeled frames + $450 / mo per additional 100k
2 week free trial


$5000 / month

For teams improving datasets for multiple models in production

Unlimited users
Custom embedding models we train for you
Shared Slack channel support
500k labeled frames + $1000 / mo per additional 100k
1M unlabeled frames + $375 / mo per additional 100k
1 month free pilot


Custom pricing

For teams improving large datasets for many models in production

All of the functionality from previous tiers, plus...
Enterprise security features like SSO, access control, and Anonymous mode
Priority customer support, solution engineering help, and biweekly syncs
100M+ frames
Custom discounts + volume pricing for large datasets

Frequently asked questions

What is a frame?

We charge based on the number of frames in the latest state of your machine learning dataset. You can think of this as the number of "rows" in your dataset, where each row can contain (for example) an image with labels on it.

There are two types of frames we bill for:
1) The number of unique labeled frames in your latest labeled training / validation / etc. dataset stored in Aquarium.
2) The number of unique unlabeled frames that you'd like to index for embedding similarity searches / targeted data collection. This is usually data collected from your production environment that your model has run inferences on.

This means we do not charge for metadata fields attached to each example like device id, timestamp, etc. We also do not charge for model inferences on these datasets. For object detection datasets, we don't change pricing per frame. However, we reserve the right to change pricing or impose limits on how many of these you can upload if it exceeds our system's ability to scale.

What if I don't have my own embeddings?

Aquarium offers a suite of pretrained models that can automatically generate embeddings on your own dataset. We can also train embedding generation models on your dataset that are fine-tuned for your data domain.

Can I upload my own embeddings?

Yes. Aquarium's client API allows users to upload their own model embeddings.

Can I use data hosted outside of Aquarium?

Yes, users can upload URLs to data hosted outside of Aquarium with a little bit of setup. All of Aquarium's functionality functions the same as long as authentication is configured correctly.

How do you handle data security?

Aquarium is SOC 2 Type 2 certified. We support SSO and other enterprise-grade authentication schemes to interface with hosted data.

In addition, we have a special "Anonymous Mode" which allows users to upload metadata to Aquarium without ever exposing their raw data.

World class ML teams trust Aquarium

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Get in touch

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