Arize AI

@arizeai

The AI engineering platform for teams shipping reliable AI agents and LLM applications. Also home to @ArizePhoenix.

San Francisco, CA

arize.com

Joined January 2020

Affiliates Replies Media

Arize AI
@arizeai
6m
Model pricing pages tell you what tokens cost, but production economics depend on how much work those tokens actually complete. ICYMI from our Arize × @FireworksAI_HQ session: we measured cost per successful task across 2,400 traced runs on Terminal-Bench across K3, GPT-5.5, and
Arize AI
@arizeai
36m
You can choose a frontier model and still ship an unreliable agent. Production behavior also depends on the context the model receives and the harness that turns its reasoning into action. We teamed up with @AtlanHQ to break down how to evaluate all three layers:
You chose the best model. Why is your agent still failing?
From arize.com
Arize AI
@arizeai
4h
How do you evaluate agent skills before and after they reach production? @CohereHealth built that loop into its clinical policy digitization system on Amazon Bedrock AgentCore, with Arize supporting the production evaluation layer. @AWS breaks down the architecture:
How Cohere Health digitizes clinical policies using Amazon Bedrock AgentCore | Amazon Web Services
From aws.amazon.com
Arize AI
@arizeai
Aug 11
OpenTelemetry’s GenAI semantic conventions are becoming a common way for frameworks and agent platforms to describe model calls, tools, retrieval, token usage, and more. Arize AX now supports those conventions natively, so gen_ai.* spans arrive as structured AI traces. Learn
00:00
Arize AI
@arizeai
Aug 10
The EU AI Act turns principles like fairness, transparency, human oversight, and robustness into evidence product and engineering teams may need to produce for a specific AI system over time. Here’s what that means for developers:
Demystifying the EU AI Act for AI product and engineering teams
From arize.com