Learn More

Arrow Right
Thanks for your submission.
We'll be in touch!
Oops! Something went wrong while submitting the form.
Contact Sales
corner angle
Arrow Right
Thanks for your submission.
We'll be in touch!
Oops! Something went wrong while submitting the form.
Request Access
corner angle
Arrow Right
Thanks for your submission.
We'll be in touch.
Oops! Something went wrong while submitting the form.
Quotient AI LogomarkLogomark Left Side

Build better
AI products fast

Logomark Right Side
Quotient quickly evaluates your generative AI products on criteria unique to you and your users so you can ship high quality products in days not months.
Get started
Right Arrow

Innovators building with Quotient

Quotient was the first product that was able to accurately and reliably test policy compliance of our AI agents. We’re now excited to continue to innovate with the confidence that all our AI solutions are meeting our high standards for customer solutions.
Head of AI, Customer Service
Quotient's platform enables us to conduct fast experimentations within our system, whether related to our generative models or influenced by our retrieval system and data pipeline. We can quickly connect these individual components back to the overall product, resulting in high quality for our customers.
CEO & Founder

Evaluation is slow and painful

> 6 Months to Deploy

typical AI product launch delay from slow iteration cycles

< 10% Test Coverage

too low for complex AI products

> 80% Wasted Dev Time

from manual data curation and testing instead of coding

Evaluate at the speed of innovation

25x faster
data curation,
automatically

Data you already have becomes reference data for evaluation & fine-tuning.

20x faster
evaluations,
fully orchestrated

Handle model, dataset, and prompt management & version control with ease.

100% personalized evaluation,
at scale

Tailor your AI products to your users with customizable evaluators.

Create high quality AI products

With Quotient, you can find the best recipes for the AI products you are cooking that meet the unique requirements of your users.
Here’s how it works:
Attempt 1Attempt 1
The low score indicates an issue with the Retrieval Augmented Generation (RAG).
Let’s try a different configuration…
Attempt 2Attempt 2
Higher score indicates that the new RAG configuration is pulling the right information for our use case!
Let’s try a new prompt template that nudges the model to do more reasoning based on that information…
Attempt 3Attempt 3
Success – we’re now getting high-score answers!
We confirm this is consistent across our entire evaluation dataset, and ship the final recipe to production.

Updates

Our partners