Built with Arize

Top enterprises and organizations leveraging Arize to achieve better production outcomes

atropos health

Atropos Health

bazaarvoice

Bazaarvoice

arize customer chime

Chime

Clearcover

Defense Innovation Unit

Etsy logo

Etsy

Flipkart

Get Your Guide

Klick

Ronin

spark nz logo

Spark

spotify logo arize customer

Spotify

Stitch Fix

Shelf Engine

Turing

vivun

Vivun

Wayfair

Zippi

Adobe

CCC Intelligent Solutions

cohere

Cohere Health

conde nast

Conde Nast

Credit-ninja

Credit Ninja

discord logo

Discord

forward financing logo

Forward Financing

gojek logo

Gojek

gpc company

GPC

Groundspeed

Groundspeed

the hartford

The Hartford

honeywell

Honeywell

Intermountain-health

Intermountain Health

jetblue

JetBlue

Legion Technology

Legion

Meesho

Mercury Insurance

Mercury Insurance

motorway

Mototway

nfx logo

NfX

Nerdy

Nerdy

Neustar

New York Life

Nextdoor

Ocurate

Predict HQ

ringcentral

RingCentral

schneider

Schneider Electric

Twilio

Upstart

Vungle

zeitview

Zeitview

ZipRecruiter

More customer stories

How GetYourGuide Powers Millions of Real-Time Rankings with Production AI

This piece is co-authored by: Martin Jewell, Senior MLOps Engineer at GetYour Guide; Greg Chase, Machine Learning Solutions Engineer at Arize AI; and Mihir Mathur, Product Manager at Tecton GetYourGuide,...

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Lou Kratz headshot

How Bazaarvoice Navigated the Challenges of Deploying an LLM App

Bazaarvoice, a top platform for user-generated content and social commerce, has leveraged AI for much of its history — and now has a pioneering LLM app in production. At Arize:Observe...

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Aparna Dhinakaran and Anu Trivedi headshots

How Flipkart Leverages Generative AI for 600 Million Users

Catering customer support for 600 million users is a feat in itself. Between sessions at this year’s Arize:Observe, Flipkart’s Anusua (Anu) Trivedi talked to Aparna Dhinakaran about the company’s challenges...

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Rebecca Hyde headshot

How Atropos Health Accelerates Research with LLM Observability

Atropos Health aims to close the evidence gap to make it easier for physicians to have access to on-demand observational studies whenever needed. We caught up with Rebecca Hyde, Principal...

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Peter Leimbigler Data Science Team Leader at Klick Consulting

What Does It Take To Pioneer Successful LLM Applications In Healthcare and the Life Sciences?

Peter Leimbigler is a Data Science Team Leader within the Consulting practice at Klick Health. As the largest independent commercialization partner in its industry, Klick pioneers new AI-powered applications for...

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Stefan Kalb Shelf Engine

Shelf Engine’s CEO On Disruptive Innovation Without Disruptive Adoption and the AI-Driven Future of Grocery Retail

Stefan Kalb is on a mission to eliminate food waste and revolutionize the grocery business. Shelf Engine – the company he co-founded and leads as CEO – has notched an...

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Industry leaders trust Arize

"Arize has nurtured an active community of LLMOps learners, professionals, and advocates that I’ve personally found very helpful to (try to) stay on top of new developments."
Peter Leimbigler Data Science Team Leader
"You have to define it not only for your models but also for your products... There are LLM metrics, but also product metrics. How do you combine the two to see where things are failing? That’s where Arize has been a fabulous partner for us to figure out and create that traceability."
Anusua (Anu) Trivedi Head of Applied AI, U.S. R&D, Flipkart
"Our big use case in Arize was around observability and being able to show the value that our AIs bring to the business by reporting outcome statistics into Arize so even non-technical folks can see those dashboards — hey, that model has made us this much money this year, or this client isn’t doing as well there — and get those insights without having to ask an engineer to dig deep in the data."
Lou Kratz Principle Research Engineer

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"For exploration and visualization, Arize is a really good tool."
Rebecca Hyde Principal Data Scientist
“Michaelangelo is Uber’s end-to-end ML platform that powers 100% business-critical ML use cases at Uber to deliver a consistent user experience across billions of rides and deliveries. Given the vital role ML plays in this process, it’s critical to have tools that build on Michalangelo’s core capabilities and help us stay ahead of potential production ML problems. We’re excited to work with Arize AI to enhance platform ML observability capabilities and make it easier to detect and resolve model performance issues.”
Kai Wang Product Lead - Uber AI Platform
"We believe that products like Arize are raising the bar for the industry in terms of ML observability. Standardized model observability will soon become a best practice and an integral part of any new machine learning projects in production, similar to what Datadog and Grafana have achieved in software engineering. We are excited to be part of this evolution of data science, as we continue working with Arize and leverage the platform’s capabilities."
Mihail Douhaniaris and Steven Mi Data Scientist and Senior MLOps Engineer, respectively
"Earlier this year, Wayfair chose Arize as its model monitoring solution...Since model monitoring is a vital component of MLOps, Wayfair’s ML platform team is working closely with Arize AI to develop a long term strategy around onboarding."
Duncan McKinnon Machine Learning Engineer 2
“The ability to quickly change what we’ve built, understand how it’s different from the previous models and know where it has problems is mission-critical … to our commitment to innovation and leadership in the increasingly privacy-focused advertising environment.”
Alok Kothari Director of Machine Learning, Adobe
"The team evaluated several options and ultimately chose Arize due to its strong support, effective onboarding process, and commitment to helping us scale up our skills to consistently leverage the tool. Arize will help us further improve our models’ performance, ensure the quality of our data, and maintain fairness and transparency in our machine learning processes."
Valeria Gomes Data Lead
"We recently deployed a model that went from inception to production in 46 days – hardly a small endeavor given the model is relied on to score over 50,000 insurance applications daily. Arize is a big part of that success because we can spend our time building and deploying models instead of worrying – at the end of the day, we know that we are going to have confidence when the model goes live and that we can quickly address any issues that may arise."
Alex Post Lead Machine Learning Engineer
"Machine learning is a discipline where few notice when everything is performing perfectly — and everyone notices when things go wrong. In that sense, it’s not a question of whether you need ML observability — you do — it’s more a matter of whether to build or buy. For us, Arize was the clear choice in terms of cost efficiency and freeing us up to achieve our broader vision."
Richard Woolston Data Science Manager
“Arize was really the first in-market putting the emphasis firmly on ML observability, and I think why I connect so much to Arize’s mission is that for me observability is the cornerstone of operational excellence in general and it drives accountability.”
Wendy Foster Director of Engineering and Data Science, Shopify
“Some of the tooling — including Arize — is really starting to mature in helping to deploy models and have confidence that they are doing what they should be doing.”
Anthony Goldbloom Co-Founder & CEO, Kaggle
"Models are never perfect; they are always going to drift based on changing behaviors, changing data, or changing source systems. Having a centralized monitoring platform like Arize is immensely beneficial."
Malav Shah Data Scientist II
"Arize really values understanding and helping the data scientist – a platform built by and for tech people – which resonates with our team."
Habib Baluwala Domain Chapter Lead for Commercial Data
“The Arize AI platform provides an intuitive UI that’s easy to use and can monitor drift and performance of all models across our most advanced communication deployments.”
Brendon Villalobos Machine Learning Technical Lead, Twilio
“It is critical to be proactive in monitoring fairness metrics of machine learning models to ensure safety and inclusion. We look forward to testing Arize’s Bias Tracing in those efforts.”
Christine Swisher VP of Data Science, Project Ronin
“As an organization, we generally build rather than buy – particularly for our AI and machine learning infrastructure. So it’s a high burden to meet, and Arize meets it in terms of helping sophisticated organizations like Shelf Engine that don’t do off-the-shelf data science.”
Stefan Kalb CEO, Shelf Engine

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