Evidently AI · Rate Limits

Evidently Rate Limits

Name: Evidently Rate Limits
Creator: Evidently AI
Keywords: ML Monitoring, LLM Observability, Data Drift, Model Performance, AI Evaluation, Data Quality, Open Source, MLOps, LLMOps, Generative AI

Evidently AI's core library is open-source and self-hosted, so there are no externally enforced API rate limits from Evidently for the OSS deployment — limits are governed by the operator's own infrastructure. The commercial platform (Expert/Enterprise) is self-hosted and rate limits are similarly infrastructure-dependent. Evidently has not published specific HTTP rate-limit headers or per-minute/per-day call caps for its Platform REST API. The following reflects known constraints and guidance from documentation; operators should size their deployments accordingly.

Evidently Rate Limits is the machine-readable rate-limit profile for Evidently AI on the APIs.io network, conforming to the API Commons Rate Limits specification.

Tagged areas include ML Monitoring, LLM Observability, Data Drift, Model Performance, and AI Evaluation.

0 Limits

ML MonitoringLLM ObservabilityData DriftModel PerformanceAI EvaluationData QualityOpen SourceMLOpsLLMOpsGenerative AI