Enterprise ready A.I. at speed
with our no-data and no-code platform.

Take a general purpose A.I. and build a specialized A.I. in hours

Abstract Cubes
Our Mission: Help you build production ready A.I. and grow beyond the novelty effect.

Features

What our platform offers

Simulate

Simulate 1000s of user's interacting with your A.I.

Collect

Use our inference end-point and analytics platform to collect KPIs. Simple 1,2,3 integrations.

Red-Team

Find the failure cases of your model automatically. Does your model provide relevant responses to your users?

Specialize

Use the simulation data or collected data to create a specialized A.I. in hours!

Integrations

We integrate with OpenAI, Claude and several Open-Source models.

A|B Testing

Find which model is best to deploy with 'what-if' scenarios.

Our prices

We only charge for the tokens you generate using our platform.

basic

Hobbyists and Hackers

Free
for ever!
  • < 10M Tokens per month
  • Analytics Platform
  • Anti-Bot Protection

Start-Up

Growing product

$1
Per 1M Tokens
  • < 1B Tokens per month
  • Analytics Platform
  • Anti-Bot Protection
  • Super-Alignment Training

Enterprise

Established Product

Contact Us
for a tailored plan
  • > 1B Tokens per month
  • Analytics Platform
  • Anti-Bot Protection
  • Super-Alignment Training
  • Dedicated Support

Join Waitlist

We slowly test our platform and we will reach out with an invitation to participate.

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FAQs

Frequently Asked Questions

Learn more about what our platform offers through some common questions.

Can I just DIY? 🪚

Aligning and specializing the models yourself also requires specialized expertise 🤓 You will need a lot of compute and trial and error. You will end up spending more money and time as compared to using our platform.

What are the benefits of using our Analyitcs platform?

We collect several KPIs(Key Performance Indiactors) and combine with active interactions from your users. We collect signals that we can use in our secret sauce 🍅 that you will be otherwise missing. Our "signal-collection" is what differentiates us that we use to align your models.

How does versioning help me avoid poor releases?

Versioning, a.k.a. A|B testing is important in figuring out whether your latest released model is up to your customer's standards and will not cause a blunder 🤦 We provide versioning within our platform to roll-back a release

What is a no-code platform? 🧑‍💻️

A platform that requires no coding experience to use. Our intuitive U.I. can create a model without using a single line of code. If integrating with our analytics platform in your current pipeline you only need to replace a line of code to point to our end-point. You can then use our platform to interface and take care of what you need.

What is super-aligned? 🦸

Super-alignment refers to the forward and backward alignment. Forward alignment implies that your model addresses your use-case and improves your KPIs, backward alignment implies that the model does not misbave, i.e. reveal secrets 🤫

What is a production-grade A.I. that performs beyond the novelty effect? ✨

Think of the last A.I. app on the market, everyone rush to try it out and the churn rate is high. We can help you identify the failure cases of the model, such as the novelty keeps-on-going and you can add value to your customers specific to their needs, as opposed to a generalist A.I. it can only entertain.

What is a MOAT 🏰 and why do I build one?

A MOAT is what differentiates you from your competitors and establishes the long-term viability of your business. Currently, the best way to build a moat is around collecting the right (i.e. Checkpoint-AI) type of data. The longer you wait, you will lose your competitive advantage.

What is vendor lock-in? 🔒

We are commited to be a zero vendor lock-in platform. You can export your data and models at any point. We provide much more than inference or data storage and we know you will stick around 🤗

What are adversarial attacks? 🥷

Adversarial attacks are a result of poor feedback from your customers. This can be a result of automated responses, i.e. bots 🤖 , bad-actors or simply confused customers 🤷 We identify such responses and can use them to our advantage in training the model.

And more

Read more at our research blog.