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.
G-Eval turns a plain-language quality criterion into a repeatable score by having the judge reason through steps first. Here's how it works, why it beats a bare 1–5 prompt, and where it still needs calibration.
Read moreBuild a recruitment chatbot that screens candidates, answers job questions, schedules interviews, and syncs to your ATS — fairly and around the clock.
Read moreThe core RAG evaluation metrics explained — answer relevancy, faithfulness, contextual precision, contextual recall, and contextual relevancy — and what each catches.
Read moreNot every eval needs a model to grade it. Here's how to decide between deterministic metrics you can trust blindly and LLM-as-a-judge scoring you have to calibrate — and why the best suites use both.
Read moreWhat a customer service chatbot actually is in 2026, how modern AI chatbots work, the main types, and how to choose one that improves support quality.
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