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Traceloop

Freemium
llmobservabilityopen sourceaidevtoolsmlopsgenerative aimonitoringdebuggingtracing

Traceloop is a powerful, developer-centric observability solution for the specific niche of LLM applications, offering a compelling open-source and freemium model.


The open-source observability platform for LLM apps, helping developers debug, test, and monitor their AI applications.

Traceloop provides a suite of open-source tools designed for developers building applications with Large Language Models (LLMs). Through its core SDK, OpenLLM, it offers automatic instrumentation to give teams full visibility into their AI systems. This allows developers to trace the entire lifecycle of a request, from user input and prompt engineering to interactions with vector databases and the final LLM output. The platform is built specifically for debugging, monitoring, and evaluating LLM-powered applications. It tracks key metrics like cost, latency, token usage, and model performance. Users can analyze traces to understand failures, create evaluation datasets to test new prompts or models, and generate high-quality data for fine-tuning. Traceloop is aimed at AI engineering and MLOps teams who need granular control and insight into the behavior and performance of their generative AI products.

Pros

  • Strong focus on the LLM developer experience
  • Core platform is open-source and can be self-hosted for free
  • Generous free cloud tier for development and small projects
  • Automatic instrumentation simplifies setup and integration
  • Supports key AI frameworks and model providers

Cons

  • Relatively new company and product
  • Highly specialized for LLMs, not a general-purpose observability tool
  • Community and documentation are still maturing
  • Usage-based pricing for the paid cloud plan can be unpredictable for large scale

Key features

  • Open-source observability for LLM applications
  • Automatic instrumentation with the OpenLLM SDK
  • Trace requests from user input to model output
  • Monitor LLM cost, latency, token usage, and performance
  • Create and manage datasets for model fine-tuning
  • Run evaluations to test prompt and model changes
  • Self-hosted and managed cloud deployment options
  • Integrates with popular AI frameworks like LangChain & LlamaIndex

Integrations

OpenAIAnthropicCohereGoogle Vertex AIAWS BedrockLangChainLlamaIndexHaystackPineconeChromaDBWeaviate

Target audience

Developers, AI engineers, and MLOps teams building applications with Large Language Models (LLMs)


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Key Metrics

Founded

2023

Headquarters

Tel Aviv, Israel

Pricing Tiers

Self-Hosted

Free

Cloud Dev

Free

Cloud Pro

$20/mo

Enterprise

Custom


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