Blog
Highlights from the Currai blog: the posts worth reading first.
A complete, code-first guide to turning OpenAI Realtime voice conversations and text-to-speech generations into readable Currai User Stories and correctly nested traces.
A step-by-step guide to importing completed Retell AI calls into Currai with signed call-ended webhooks—without adding capture code to the live voice agent.
A step-by-step guide to importing completed Vapi calls into Currai with an authenticated webhook—without adding capture code or sharing a Vapi private API key.
Browse implementation notes, observability guides, product decisions, and workflow ideas by topic.
Multi-turn support quality depends on context, policy accuracy, escalation, and consistency. Currai traces make those conversations eval-ready.
Read moreEvaluate a fine-tuned model against its base using production traces, representative datasets, quality metrics, cost, and regression tests.
Read moreAI evals are not just engineering tests. Currai helps PMs use production traces, rubrics, and domain judgment to improve AI product quality.
Read moreAI evals work best when product, support, engineering, and domain experts share traces, rubrics, and quality decisions in Currai.
Read moreLearn how to mine production traces for recurring agent failures, turn the patterns into evals, and close the AI agent improvement loop with Currai.
Read more