Blog
Highlights from the Currai blog: the posts worth reading first.
Use real production conversations to find agent failures, make focused prompt changes, build better evals, and verify that user outcomes improve.
Monitor customer success agents with end-to-end traces, conversation outcomes, groundedness, escalation quality, policy compliance, latency, and cost.
A beginner-friendly, code-first guide to turning Vapi browser calls into Currai sessions, conversation User Stories, and correctly nested voice-agent traces.
Browse implementation notes, observability guides, product decisions, and workflow ideas by topic.
Evaluate a fine-tuned model against its base using production traces, representative datasets, quality metrics, cost, and regression tests.
Read moreSummarization looks easy to grade and isn't — a fluent summary can be unfaithful, incomplete, or subtly wrong. Here's how to score the two things that actually matter: faithfulness to the source and coverage of what mattered.
Read moreA step-by-step build for a chatbot that answers questions from your documents with RAG — plus the part most tutorials skip: how to know its answers are grounded and correct instead of confidently wrong.
Read moreA step-by-step plan to implement customer service automation: pick the right processes, prepare knowledge, roll out in stages, and measure accuracy.
Read moreWhat 'training ChatGPT on your data' really means in 2026 — retrieval, custom GPTs, and fine-tuning — and how to build a grounded assistant that cites sources.
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