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.
Learn how to design an embeddable payments SDK for an AI app with credit wallets, secure browser sessions, usage debits, webhooks, idempotency, and cost reconciliation.
Read moreLogs tell you a line ran. Traces tell you what the model saw, said, and cost across the whole request. Here's why LLM apps need tracing, not more print statements.
Read moreYour LLM calls don't all live in Python. Currai ingests traces over plain HTTP and OTLP, so any language that can make a request can send traces — here's how.
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