Currai solves the challenges of monitoring and evaluating Large Language Model (LLM) applications by providing comprehensive observability. Developers often struggle with understanding how their LLM prompts perform in production and lack visibility into the underlying data usage and costs associated with these models. Currai addresses this issue by allowing users to trace every prompt, token, and tool call, providing insights that ensure trust and transparency in LLM applications. Key features include: - **Drop-in Python & TypeScript SDKs:** Easily integrate Currai into your existing apps to start tracking performance immediately. - **Full Traces and Token Usage:** Get complete visibility over each LLM call, including inputs, outputs, and associated token costs in a single view. - **A/B Testing Capabilities:** Experiment with different prompt versions and evaluate their performance in real-time. - **Session Tracking:** Group multi-turn conversations by session and user for enhanced analytics. - **Plan-Based Data Retention:** Choose how long you want to retain your tracing data according to your plan. - **Compatibility with Existing Tools:** Currai works seamlessly with Langfuse and OpenTelemetry, making it easy to migrate existing setups. Notable alternatives include tools like OpenTelemetry and Prometheus, which focus more broadly on observability and may not specifically cater to LLMs. Currai stands out by providing specialized features tailored to LLMs, with a strong emphasis on ease of integration and functionality specific to language models. As for pricing, Currai operates on a usage-based model where you pay for the processed data rather than a per-trace fee. This aligns the cost with the actual data volume you utilize, making it more economical for varying workloads. FAQs: 1. **What is Currai?** Currai is a platform that provides observability for LLM applications through detailed tracing and analytics. 2. **How quickly can I get started?** You can start tracking your first trace in about five minutes by installing the SDK and setting up a single LLM call. 3. **Is my application performance impacted?** No, tracing is done in the background and doesn't slow down your application's response times. 4. **What programming languages does Currai support?** It currently supports Python and TypeScript and is compatible with Langfuse and OpenTelemetry. 5. **How is the pricing structured?** Pricing is based on the actual data processed, ensuring you only pay for what you use, rather than a flat fee per trace.
