Currai

Currai is a platform for teams building AI features that rely on large language models. It gives you one place to trace every LLM call, test prompts before they go live, and measure how well your AI actually performs. Instead of digging through scattered logs or guessing whether a new prompt is better, you get structured data on latency, cost, token usage, and output quality.

The tool works by capturing hierarchical traces of every LLM interaction — including tool calls, retrieval steps, and model responses. You can filter by user, session, environment, or custom tags. Currai also includes a prompt registry that lets you manage prompts outside your codebase, deploy new versions with one click, and roll back instantly if something breaks. For evaluation, you can run LLM judges, custom heuristics, or human reviews on production traffic or experimental prompts. A/B testing splits real user requests between prompt versions so you can compare quality, speed, and cost side by side.

Currai is built for engineering teams that ship AI-powered products — whether you're building a customer support chatbot, a code assistant, or a content generation tool. It helps you catch failures early, understand why a response was bad, and iterate on prompts without redeploying your entire app. If you're tired of blind deployments and manual reviews, Currai gives you the data to make informed decisions.