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 chat projects turn uploaded PDFs, spreadsheets, documents, and code into a reusable knowledge base. Learn how RAG, project memory, instructions, and source citations keep every chat grounded.
Read moreHow startups should approach LLM evaluation in 2026 — the minimum viable eval setup, what to measure, and how to build a quality loop without a big team.
Read moreChatbots fail across a conversation, not in a single reply. Here are the metrics that actually catch chatbot failures — and why turn-level scoring alone always misses them.
Read moreA practical review of Intercom's Fin AI agent in 2026: how it works, its resolution-based pricing, where it fits, and when to consider alternatives.
Read moreUse the ChatGPT API as an LLM judge with stable rubrics, structured scores, bias controls, human calibration, and production trace evaluation.
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