Evaluate, improve and ship your AI products through fast experimentation cycles.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
Build better AIÂ products fast
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
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.
Graham Ganssle
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.
Hao Sheng
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:
The low score indicates an issue with the Retrieval Augmented Generation (RAG).
Let’s try a different configuration…
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…
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.