Traceloop - LLM Reliability Platform

Description

Traceloop is a platform designed to enhance the reliability of LLM applications by turning evaluations and monitoring into a continuous feedback loop. This ensures that every release of your application gets better over time. The platform addresses common issues such as ad-hoc scores and gut-check metrics that leave results in doubt and waste time. Traceloop provides visibility into model performance, catching failures before they reach production.

With Traceloop, users can start tracking their LLM applications in seconds with just one line of code. This provides live visibility into prompts, responses, latency, and more, without any setup hassle. The platform runs quality checks automatically using built-in metrics for faithfulness, relevance, and safety, allowing users to get a baseline understanding of model quality without writing tests.

Traceloop allows users to define quality on their own terms by annotating real examples and training custom evaluators. This makes quality a part of the pipeline, running evaluations automatically on every pull request or in real-time as the app runs. The platform is enterprise-ready, compliant with SOC 2 and HIPAA, and can be deployed in various environments including cloud, on-premise, or air-gapped setups.

Built on open standards like OpenTelemetry, Traceloop offers transparency without lock-in. It supports multiple programming languages and integrates with over 20 providers, vector databases, and frameworks. The platform is open source, with its OpenLLMetry SDK available on GitHub. Traceloop offers a freemium pricing model, allowing free usage for up to 50,000 spans per month, with no seat limit and all features open.

Traceloop's Core Features

• Continuous feedback loop for LLM apps

• Real-time insights into model performance

• Automatic quality checks with built-in metrics

• Customizable quality definitions

• Enterprise-ready with SOC 2 and HIPAA compliance

• Open standards with OpenTelemetry

• Supports multiple programming languages

• Integrates with 20+ providers and frameworks

• Freemium pricing model

• Open source with OpenLLMetry SDK

How to use Traceloop?

1. 1

   Configure: Add one line of code for tracking

2. 2

   Use: Monitor prompts, responses, and latency

3. 3

   Optimise: Run automatic quality checks

4. 4

   Deploy: Use in cloud, on-prem, or air-gapped environments

Traceloop's Use Cases

• Real-time monitoring
• Quality assurance
• Custom evaluations
• Enterprise deployment
• Open source development

FAQ from Traceloop

• What is Traceloop?

  Traceloop is a platform that enhances LLM app reliability by transforming evaluations and monitoring into a continuous feedback loop.

• How does Traceloop improve model quality?

  Traceloop provides real-time insights and automatic quality checks, allowing users to define custom quality metrics.

• Is Traceloop enterprise-ready?

  Yes, Traceloop is SOC 2 and HIPAA compliant and can be deployed in various environments.

• What programming languages does Traceloop support?

  Traceloop supports Python, TypeScript, Go, and Ruby.

• What integrations does Traceloop offer?

  Traceloop integrates with over 20 providers, vector databases, and frameworks.

• Is Traceloop open source?

  Yes, Traceloop is open source and offers the OpenLLMetry SDK on GitHub.

• What is the pricing model for Traceloop?

  Traceloop offers a freemium model with free usage for up to 50,000 spans per month.

• How quickly can I start using Traceloop?

  You can start tracking your LLM applications in seconds with just one line of code.