The best Qualdo-MQX alternatives

Weave suits teams building or operating production AI agents that need tracing, evaluations, interaction monitoring, or prompt comparisons.

Evidently AI suits teams evaluating or monitoring language models, RAG applications, agents, or predictive ML workflows.

Opik suits teams developing applications or agents that call an LLM and need to inspect, evaluate, and monitor their behavior.

NannyML suits teams monitoring deployed machine-learning models, especially when ground truth is delayed or absent.

It suits teams evaluating and monitoring LLM applications in production, especially those needing configurable deployment options or integrations.

Langfuse suits teams building AI agent applications that need tracing, prompt management, and evaluation tools.

LangWatch suits AI teams working on agents, including developers, product owners, QA, and domain experts involved in evaluation workflows.

OpenLIT suits developers who want to observe LLM applications, prompts, evaluations, and costs.

SUPERWISE suits engineers and AI teams building language-model applications and agents.

LangSmith suits teams developing AI agents that need evaluation, prompt tools, tracing, and production monitoring.

It is designed for cross-functional AI teams, including product managers who want to define and analyze evaluations without code and developers who…

It suits teams building or operating AI applications that need provider routing, request tracing, or cost visibility.

Braintrust is intended for teams running AI agents in production, from early-stage projects to enterprise deployments.

Laminar suits teams building AI agents that need to trace model and tool activity, investigate runs, or evaluate changes against datasets.

Fiddler AI is aimed at enterprises managing AI agents and predictive applications at scale, including teams that need monitoring, guardrails, and…

Memoturn suits teams building LLM applications that need to inspect production traffic, monitor spending, evaluate quality, and manage prompts.

Arize AX suits teams working to observe, evaluate, and improve AI agents in production.

Arthur suits enterprise teams that need to find and monitor AI agents, apply governance policies, or manage agent deployments alongside sensitive…

Galileo is designed for engineers, product managers, and subject matter experts building AI applications.

Phoenix suits teams that need to inspect AI application traces and compare evaluation results across versions.

It suits AI platform teams, AI engineers, domain experts, and risk and governance teams that need production agent visibility.

Pulsar is aimed at software engineers, data scientists, and machine-learning engineers monitoring deployed models.