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.
The parts every LLM eval framework needs — datasets, metrics, a runner, and a results store — and an honest look at when to build your own versus when a homegrown harness quietly becomes the thing you maintain instead of your product.
Read moreCompare the best Crisp alternatives for AI customer support in 2026 on AI answers, channels, integrations, pricing, and how they handle knowledge and escalation.
Read moreWhat the popular LLM benchmarks actually measure, why a high leaderboard score doesn't mean your app will be good, and how to read benchmarks as a starting point instead of an answer.
Read moreAI agent evals need more than a final answer score. Learn how to evaluate tool calls, transcripts, outcomes, regressions, non-determinism, and production traces.
Read moreThe best AI eval tools for CI/CD catch prompt, model, retrieval, and agent regressions before deploy. Compare Currai, Promptfoo, Braintrust, Langfuse, and Phoenix.
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