Generative AI has been hailed as a disruptive force, but it has fallen short of expectations. Organizations have invested heavily in hopes of reaping transformative benefits, yet widespread adoption and real impact have failed to materialize and match the hype.
So, what’s going on?
As it stands, the current suite of Large Language Models (LLMs) are not sophisticated enough to solve real-world business challenges right out of the box. While these models perform well on academic benchmarks, addressing practical problems requires more context through prompts, retrieval augmentation, or fine-tuning. For developers of generative AI products, this process has been more of an art than a science, leading to slower, “vibes-driven” iteration cycles and subpar results.
We’re on a mission to change all that, and help developers build better AI products, faster.
Hello World, we’re Quotient 👋
Every developer understands that for a change in their system to be strategic rather than impulsive, it is crucial and essential to test its impact on the desired outcome. The ability to do this seamlessly, swiftly, and reliably results in flywheels of iterative improvements that ultimately create disruptive products that delight users.
Quotient equips all AI developers with the tools to achieve just that. With Quotient, they can swiftly gauge the effectiveness of their cutting-edge generative AI solutions to meet the unique requirements of each user or customer.
Quotient brings an end to one-size-fits-all evaluation
With Quotient, we're not just offering a tool; we're offering a solution that bridges the gap between the potential of generative AI and its real-world impact.
Quotient offers AI developers the capability to evaluate their AI products with specialized datasets and frameworks, which can be customized or ready-to-use, and tailored to their organization. By addressing challenges in evaluation management, version control, and orchestration, Quotient streamlines assessments of models, prompts, and retrieval augmentation through rapid, data-driven iteration cycles.
With Quotient, you can achieve:
- 25x faster data curation, automatically. The data you already have becomes reference data for evaluation and fine-tuning.
- 20x faster evaluations, fully-orchestrated. You can handle model, dataset, and prompt management, and version control with ease.
- 100% personalized evaluation, at scale. Get ready to tailor your AI products to your users with customizable evaluators.
Accelerating evaluation to the speed of innovation
Our ambition to build Quotient is rooted in first-hand knowledge of what is necessary to build and launch powerful generative AI products.
At GitHub, our founders brought one of the most disruptive AI products to market: GitHub Copilot. They accomplished this by developing an evaluation infrastructure that empowered interdisciplinary teams of engineers, researchers, and product leaders with the ability to get fast, quantitative feedback on their work, and ultimately release products that surpassed audacious goals.
We know that shipping based on vibes and manual trial and error is not enough. We saw the road ahead — and we believe that the ability to understand, anticipate, and improve the performance of AI products is key to unlocking their adoption at scale.
We are committed to helping those embarking on similar journeys reach their goals. We can’t wait to see what you’ll achieve.
Let’s get started! 🚀
- Julia, Freddie, and Quotient’s Founding Team
