Traceloop
Free tierLLM reliability platform that turns evals and monitors into a continuous feedback loop
Key strengths
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Recent changes
- Plans updated: Free tier: $0/mo, up to 50K spans/month, up to 5 seats, 24-hour data retention. Enterprise: custom pricing (contact sales), >50K spans/month, unlimited seats, custom data retention, SOC 2, on-prem option. Available on AWS, GCP, and Azure Marketplaces.
- Models updated: Agnostic — supports OpenAI, Anthropic, Gemini, Bedrock, Ollama, and 20+ providers
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Traceloop — Technical Use Cases
1. Distributed LLM Tracing in Production
Instrument multi-step LLM pipelines (e.g., RAG workflows using LangChain + Pinecone) with OpenLLMetry. Every span — retrieval, prompt construction, model call, tool invocation — is captured and correlated into a single trace, enabling root-cause analysis of latency or quality regressions.
2. Automated Evaluation in CI/CD
Integrate Traceloop's evaluation engine into GitHub Actions or other CI systems. Run faithfulness, relevance, and safety evaluations against a golden dataset on every pull request, blocking deploys that fall below quality thresholds.
3. Multi-Provider Benchmarking
Use Traceloop's provider-agnostic instrumentation to compare outputs, latency, and cost across OpenAI, Anthropic, Gemini, and Amazon Bedrock — all within a unified trace view — to inform model selection decisions.
4. Compliance-Constrained Deployments
For teams in regulated industries, deploy Traceloop self-hosted or on-prem (Enterprise) in an air-gapped environment. SOC 2 and HIPAA compliance documentation is available for enterprise customers.
5. Agent & Multi-Framework Observability
Trace agentic workflows built with CrewAI or LlamaIndex, capturing inter-agent calls, tool use, and vector DB queries (Pinecone, Chroma) as structured spans — without custom instrumentation code.
6. Marketplace-Native Deployment
Provision Traceloop directly from AWS, GCP, or Azure Marketplaces to consolidate billing and satisfy cloud-committed-spend requirements.