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.
AI 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 moreAI observability should do more than store traces. Currai turns traces into active signals for quality, cost, latency, prompts, tools, and evals.
Read moreHow AI chatbot pricing really works in 2026 — per seat, per message, per resolution, and usage models — and how to model your true cost before buying.
Read moreStateful agent evals need more than a final answer score. Currai ties agent steps, tool calls, sessions, cost, latency, and eval results back to the production trace.
Read more