Blog
Practical posts on tracing, evals, prompt changes, token cost, and the production habits that keep AI products explainable.
Highlights from the Currai blog: the posts worth reading first.
Why AI agent evaluation still needs humans in 2026, where to put them in the loop, and how to combine human review with automated evals on production traces.
A practical field guide to LLM evaluation tools — what each category is good at, where they break down, and how to pick one that survives contact with production traffic.
The best AI observability tools in 2026 compared on evaluation depth, quality-aware alerting, drift detection, cost tracking, and the production-to-eval loop.
Browse implementation notes, observability guides, product decisions, and workflow ideas by topic.
A practical look at automated customer service in 2026 — the real ROI, the full cost picture, and how to implement it so the savings are real, not on paper.
Read moreWhat makes an AI chatbot HIPAA-compliant, the safeguards healthcare teams need, and how to evaluate platforms — with the caveat that compliance is how you operate it.
Read moreWhat makes an AI chatbot GDPR-compliant, the data rights and safeguards to require, and how to evaluate platforms — with the caveat that compliance is how you operate it.
Read moreWhat an IT support chatbot does, how it deflects tickets and resets access safely, and how to choose one that helps employees without creating security risk.
Read moreHow drag-and-drop chatbot builders work, what to look for in a no-code builder, and where visual flows end and AI answers begin.
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