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LLM observability

Currai

LLM observability and prompt A/B testing platform.

Source rating 5.0 (74) 0 views 0 saves Paid
LLM observability LLM tracing Prompt tracing
More categories (6)
Token cost tracking Langfuse alternative OpenTelemetry LLM AI observability LLM Monitoring Prompt A/B testing
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From $8 / mo

Verdict

A quick read before you dig into the full page.

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LLM observability and prompt A/B testing platform
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Paid · From $8 / mo

Overview

Currai is an observability and tracing platform designed for LLM applications. It helps developers move away from basic print statement debugging by tracing every prompt, token, and tool call in a single view. The platform enables monitoring production traffic, calculating costs based on processed bytes, running evaluations, and A/B testing prompt versions live without requiring any local infrastructure to run. It offers drop-in Python and TypeScript SDKs and is byte-compatible with Langfuse and OpenTelemetry, making it easy to integrate or migrate existing projects.

Currai screenshot

Access & connections

Where you can use Currai.

Platforms

Web

Capabilities

What this tool accepts, produces, and is strongest at.

Highlights

  • Full tracing of prompts, tokens, and tool calls in one view
  • Production prompt A/B testing and evaluation scoring
  • Background trace batching and flushing to prevent application slowdown
  • Byte-compatible drop-in support for Langfuse and OpenTelemetry
  • Pricing model calculated on processed data volume (bytes) instead of flat trace counts

FAQ 5

What is Currai?
Currai is an observability and tracing platform designed for LLM applications. It helps developers move away from basic print statement debugging by tracing every prompt, token, and tool call in a single view. The platform enables monitoring production traffic, calculating costs based on processed bytes, running evaluations, and A/B testing prompt versions live without requiring any local infrastructure to run. It offers drop-in Python and TypeScript SDKs and is byte-compatible with Langfuse and OpenTelemetry, making it easy to integrate or migrate existing projects.
How to use Currai?
To use Currai, install the SDK via pip or npm, initialize it using your public and secret keys, and wrap your LLM calls using the trace and generation methods to start capturing inputs, outputs, and token usage.
Will tracing slow down my app?
No. Traces are batched and flushed in the background, so instrumentation never blocks a request. In short-lived processes, you call flush() or flush_async() before exit to make sure everything is sent.
How long does it take to get my first trace?
About five minutes. Install the SDK with pip install currai or npm i currai, paste your public / secret key pair, and wrap a single LLM call. The first request you make shows up in the dashboard right away.
How is pricing calculated?
Usage is billed on the data Currai actually processes—measured in processed bytes—not on a flat per-trace fee. Large traces and tiny traces are priced for what they are, so your cost tracks real volume instead of row counts.
Currai From $8 / mo
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