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.
Testing an LLM app isn't like testing normal software — outputs are non-deterministic and open-ended. Here are the testing methods that actually work: unit, regression, adversarial, and production, and how they fit together.
Read moreA 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.
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