Building on my previous blog post, I’d like to share more examples to help readers develop intuition around AI testing. This time, rather than focusing on RAG apps, we’ll dive into deployment testing. The goal is to illustrate how deployment testing can provide deeper insights into the consistency of an AI-powered application after it reaches […]
Last week, Distributional joined other cutting-edge companies at NVIDIA GTC, where we chatted with other leaders in AI about what they’re building and the challenges they’re facing, reconnected with friends and former colleagues, and shared a live demo of the latest capabilities at our booth. With over 17K people showing up to Jensen Huang’s keynote […]
While confidence may be hindering AI progress at your organization, there is hope. The answer lies in adaptive testing.
To unlock the full potential of AI, you need to be confident in your apps’ behavior from development to deployment to continued usage.
Insight into how Distributional acts as an interpreter for AI, allowing product teams to statistically define consistency of AI application behavior.
Here’s what’s different about the new enterprise AI platform.
When it comes to RAG applications, understanding behavior doesn’t need to be a black box.
The unique characteristics of GenAI systems demand a fresh perspective on how we build, deploy, and maintain these applications.
Erin LeDell and Bonney Pelley bring decades of experience across enterprise AI to meet rising demand for Distributional’s platform/
We’re excited to announce that Bonney Pelley has joined Distributional as Chief Operating Officer.
We’re excited to announce that Erin LeDell has joined Distributional as Chief Scientist.
What do AI leaders really think about AI today? In a three-part series, we’re sharing the insights we’ve gleaned from over 1,000 hours of conversations with AI leaders at more than 100 Fortune 500 enterprises. This third post focuses on why enterprise problem that requires an enterprise solution.
What do AI leaders really think about AI today? In a three-part series, we’re sharing the insights we’ve gleaned from over 1,000 hours of conversations with AI leaders at more than 100 Fortune 500 enterprises. This second post focuses on why all ML and AI use cases need standardized testing.
What do AI leaders really think about AI today? In a three-part series, we’re sharing the insights we’ve gleaned from over 1,000 hours of conversations with AI leaders at more than 100 Fortune 500 enterprises. This first post focuses on why generative AI creates unique testing challenges.
We’ve made a lot of progress over the last year at Distributional. Since raising our seed round, we have validated the enterprise need for confidence in AI applications, grown our team, and started deploying our enterprise testing platform to address this problem in collaboration with a dozen design partners. I couldn’t be more proud of […]
Frances Schwiep and Vin Sachidananda from Two Sigma Ventures share how Distributional bridges the AI confidence gap
Distributional secures $19M in Series A funding and debuts the industry’s only enterprise AI testing platform
Our mission is to empower our customers to actively make their AI-based products more safe, reliable, and secure, before they deploy them. We aim to catch harm before their customers or users do
We raised $11M in funding to support our mission to make AI safe, reliable and secure.
Noah Carr from Point72 Ventures shares his take on how testing AI systems is distinct from testing traditional software, and why this requires a purpose-built solution.
Martin Casado and Matt Bornstein of a16z explain why they believe lack of confidence in AI is a critical barrier to enterprise adoption and how Distributional will solve this problem.