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Arize AI
ML and LLM observability — detect drift, monitor performance, debug production AI.
0Free-Limited
AI Observability
Overview
Arize AI is an ML observability platform for monitoring model performance, detecting data drift, and debugging production AI issues across both traditional ML and LLM applications.
Key Features
- Real-time feature and prediction drift detection
- LLM tracing and span monitoring via Phoenix
- Automated data quality checks and alerts
- Embedding visualization for NLP and CV models
- A/B model comparison in production
- Integrates with MLflow, SageMaker, Vertex AI
Real-World Workflows
Monitor an LLM app for quality degradation
- 1Instrument your app with the Arize SDK or OpenInference
- 2Log spans: input, output, latency, and retrieved context
- 3Set up monitors for hallucination rate and context relevance
- 4Get Slack/PagerDuty alerts when quality drops below threshold
Getting Started
pip install arize
from arize.api import Client
client = Client(space_key='...', api_key='...')
client.log(
model_id='my-llm-app',
model_type=ModelTypes.GENERATIVE_LLM,
prediction_label='Great answer',
features={'query': 'What is MLOps?'}
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