Arize AI
@arizeai
The AI engineering platform for teams shipping reliable AI agents and LLM applications. Also home to @ArizePhoenix.
Enterprise AI succeeds when teams can turn a promising demo into a reliable production system that delivers measurable business value. At Arize Observe, @CVSHealth shared how evaluation, observability, governance, and reusable engineering practices help organizations move beyond- @HamelHusain keeps stopping eval reviews for the same reason: the model isn't broken, but the product is. In part 2 of our series Rise of the Agent Engineer, Hamel walks through why ambiguous inputs, generic metrics, and disconnected reviews make AI evaluations misleading, and
- What if your agents got better every time they failed? Today, we’re launching Signal. It continuously reviews production traces, finds issues, and turns them into an investigation with evidence, root cause, and a proposed fix. Your engineers decide what ships. Signal gets them
- Arize + @FireworksAI_HQ traced 2,400 agent runs across K3, GPT-5.5, and 8 more models to measure cost per successful task and test routing strategies. The big lesson? Per-token pricing leaves retries, tool failures, and unfinished runs outside the headline number. Join the live
