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Join us on July 11th for Arize:Observe @ Shack15 →

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THE AI OBSERVABILITY & LLM EVALUATION PLATFORM

Monitor, troubleshoot, and evaluate your
LLM models

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TOP AI COMPANIES USE ARIZE

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SURFACE. RESOLVE. IMPROVE.

Catch model issues, troubleshoot root causes, and continuously improve
performance

MONITORS

DASHBOARDS

EVAL & PERFORMANCE TRACING

EXPLAINABILITY & FAIRNESS

EMBEDDINGS & RAG ANALYZER

LLM TRACING

FINE TUNE

PHOENIX OSS


LLM OBSERVABILITY


LLM OBSERVABILITY

Task-Based LLM Evaluations Troubleshoot LLM Traces & Spans Diagnose Retrieval
and RAG workflows Prompt Iteration & Troubleshooting
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TASK-BASED LLM EVALUATIONS

Easily evaluate tasks performance on hallucination, relevance, user frustration,
toxicity, and truthfulness

Gain deeper insight with eval explanations to debug and troubleshoot LLM evals


Explore in platform Explore in notebook


TROUBLESHOOT LLM TRACES & SPANS

Get visibility into your conversational workflows withLLM Tracing – support for
LangChain, LlamaIndex and LLM Otel tracing options.

Find performance bottlenecks in each step and the entire system


Explore in platform Explore in notebook


DIAGNOSE RETRIEVAL AND RAG WORKFLOWS

Intuitive tools to visualize embeddings alongside knowledge base embeddings
for RAG Analysis

Quickly identify missing context in your knowledge base to improve chat
performance.


Explore in platform


PROMPT ITERATION & TROUBLESHOOTING

Surface prompt templates associated with poor responses

Easily iterate on prompt templates and compare their performance in Prompt
Playground before deploying a new version


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ML OBSERVABILITY


ML OBSERVABILITY

Faster Root Cause Analysis Automated Model Monitoring Embedding & Cluster
Evaluation Dynamic Dashboards
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FASTER ROOT CAUSE ANALYSIS

Instantly surface up worst-performing slices of predictions with heatmaps

Always ensure your deployed model is the best performing one


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AUTOMATED MODEL MONITORING

Monitor model perfomance with variety of data quality, drift and performance
metrics, including custom metrics

Zero setup for new model versions and features, with adaptive thresholding based
on your model’s historical trends


Explore in platform


EMBEDDING & CLUSTER EVALUATION

Monitor embedding drift for NLP, CV, LLM, and generative models alongside
tabular data

Interactive 2D and 3D UMAP visualizations isolate problematic clusters for
fine-tuning


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DYNAMIC DASHBOARDS

Quickly visualize the health of your models with an array of dashboard
templates, or build a fully customized dashboard

Keep stakeholders in-the-know about model impact and ROI with at-a-glance
dashboards


Explore in platform

“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

“We believe that products like Arize are raising the bar for the industry in
terms of ML observability.”

Mihail Douhaniaris & Steven Mi
Data Scientist & MLOps Engineer, Get Your Guide

“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

“The strategic importance of ML observability is a lot like unit tests or
application performance metrics or logging. We use Arize for observability in
part because it allows for this automated setup, has a simple API, and a
lightweight package that we are able to easily track into our model-serving API
to monitor model performance over time.”

Richard Woolston
Data Science Manager, America First Credit Union

“Arize is a big part of [our project’s] 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, Clearcover

“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

“I’ve never seen a product I want to buy more.”

Sr. Manager, Machine Learning
Scribd

“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

“We believe that products like Arize are raising the bar for the industry in
terms of ML observability.”

Mihail Douhaniaris & Steven Mi
Data Scientist & MLOps Engineer, Get Your Guide

“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

“The strategic importance of ML observability is a lot like unit tests or
application performance metrics or logging. We use Arize for observability in
part because it allows for this automated setup, has a simple API, and a
lightweight package that we are able to easily track into our model-serving API
to monitor model performance over time.”

Richard Woolston
Data Science Manager, America First Credit Union

“Arize is a big part of [our project’s] 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, Clearcover

“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

“I’ve never seen a product I want to buy more.”

Sr. Manager, Machine Learning
Scribd

“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

“We believe that products like Arize are raising the bar for the industry in
terms of ML observability.”

Mihail Douhaniaris & Steven Mi
Data Scientist & MLOps Engineer, Get Your Guide

“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


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