Blog
Highlights from the Currai blog: the posts worth reading first.
Use real production conversations to find agent failures, make focused prompt changes, build better evals, and verify that user outcomes improve.
Monitor customer success agents with end-to-end traces, conversation outcomes, groundedness, escalation quality, policy compliance, latency, and cost.
A beginner-friendly, code-first guide to turning Vapi browser calls into Currai sessions, conversation User Stories, and correctly nested voice-agent traces.
Browse implementation notes, observability guides, product decisions, and workflow ideas by topic.
A practical 2026 guide to adding an AI chatbot to your website: what to look for, how to set it up, and how to make sure it gives accurate answers.
Read moreCurrai helps AI teams replace subjective launch debates with traces, eval scores, prompt versions, cost, latency, and clear quality evidence.
Read moreGolden datasets get better when they come from real failures. Currai helps teams turn production traces and human review into durable eval cases.
Read moreMulti-turn support quality depends on context, policy accuracy, escalation, and consistency. Currai traces make those conversations eval-ready.
Read moreAI evals are not just engineering tests. Currai helps PMs use production traces, rubrics, and domain judgment to improve AI product quality.
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