Tracing
Follow requests across applications, models and tools.
Solutions / AI Observability
See how your intelligent systems behave.
Observability across AI applications, agents, models and infrastructure.
Performance
Understand latency, throughput and failure patterns.
Cost
Track model and infrastructure consumption.
Quality
Monitor AI behavior and evaluation signals over time.
Frequently Asked Questions
Questions about AI Observability
What is AI observability?
AI observability provides visibility into the behavior, performance, reliability, cost, and quality of AI applications, models, agents, and supporting infrastructure.
What should enterprises monitor in AI applications?
Enterprises can monitor traces, latency, throughput, errors, model behavior, token usage, cost, evaluation results, and other reliability signals.
How can organizations monitor LLM cost and latency?
Organizations can instrument model requests and correlate usage with latency, token consumption, model selection, infrastructure utilization, and application workloads.
How does AI observability improve reliability?
AI observability helps teams identify failures, performance regressions, unexpected model behavior, cost increases, and other operational issues before they become persistent problems.