Pricing

Starter

Free

No charge for academics, hobbyists, and practitioners starting a project

1 user
Up to 10,000 datapoints
Support for image, 3D, audio data types
Projects are public with unlimited viewers
Community support through Slack group

Team

$500 / month

Billed annually, or $600 month-to-month

Up to 5 users
10,000 datapoints included
+ $100 / month per additional 10,000 datapoints
Projects are private and permissioned
Labeling provider and AutoML integrations
2 week free trial
Dedicated Customer Success manager

Enterprise

$1000 / month

Annual billing only

Unlimited users
100,000 datapoints included
+ $800 / month per additional 100,000 datapoints
Advanced user roles and permissions
Shared Slack channel support
SSO + enterprise data security (Anonymous mode)
World-class ML teams trust Aquarium

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.

Can I upload my own embeddings?

Yes. Aquarium's client API allows users to upload their own model embeddings. In fact, we prefer it! Embeddings extracted from your own model tend to be better suited for your specific dataset and task.

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 works without needing to store or host sensitive raw data on Aquarium servers. 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.

Does Aquarium offer on-prem or VPC deployments?

We currently do not offer on-prem or VPC deployments. We find that Anonymous Mode satisfies the security needs of our most restrictive customers while also scaling well to massive datasets. However, we may examine supporting VPC deployments in the near future. If you're interested, talk to us.