How Arize has helped businesses like yours.
Powering the world’s leading AI teams
Featured case studies
How Tripadvisor is building the AI product development lifecycle for agentic travel
Rahul Todkar talks about why production AI needs observability, evals, and governance across both traditional ML and LLM-based agents.
How LG U+ uses eval-driven development to continuously improve AI agents.
30 million subscribers served
+26%
in agent accuracy (from 70% to 96%)
“We adopted an evaluation-driven development approach with Arize AX and continuously improved performance by building evaluation datasets. Arize has been essential for building AI for 30 million subscribers.”
MinKyu Ha
Team Lead AI Contact Center (AICC)
27M
Monthly visits to TheFork’s app for restaurant discovery
“Thanks to visibility in Arize, we were able to intervene before an issue reached production.”
Amir Bitaraf
Senior Machine Learning Engineer
40%
improvement in accuracy of AI responses
Scaled 15+
production-ready AI use cases in the first 6 months
>500%
ROI savings with Arize AX in one year
The agent feedback loop, in your inbox.
New playbooks, field notes, and frameworks for building reliable AI agents.
Browse all customer stories
- How TheFork uses evals to boost conversions with Arize AX on AWS TheFork uses Arize AX to trace and evaluate production AI systems, helping teams catch regressions, reduce latency, govern costs, and iterate faster across retrieval, guardrails, and LLM-powered experiences.
- How Tripadvisor is building the AI product development lifecycle for agentic travel Rahul Todkar talks about why production AI needs observability, evals, and governance across both traditional ML and LLM-based agents.
- How LG Uplus is building better AI customer service agents with evaluation-driven development LG Uplus' MinKyu Ha on why user feedback, domain experts, and continuous evaluation have become essential to building AI for 30 million subscribers
- How Booking.com scales AI observability with Arize Building an AI-native observability stack for agentic AI and traditional ML at Booking.com
- How Handshake deployed and scaled 15+ LLM use cases in under 6 months with Arize AX Handshake built a centralized LLM orchestration layer integrated with Arize AX for tracing and evals, enabling teams to ship 15+ production AI use cases in six months while maintaining reliability, safety, and cost control.
Don’t ship vibes.
Arize gives AI teams observability and evals to understand and improve agent performance.
