PromptLayer

Debugging AI failures

Identify silent retry storms, stalled tool calls, and cost spikes that standard monitoring misses.

Multi-step agent workflows

Follow end-to-end execution across agents, tools, and providers with nested spans and sub-agents.

Cost tracking and optimization

Monitor token usage and spend by model, provider, project, or individual request.

Performance monitoring

View p50/p95 latency alongside cost to catch regressions before they hit your invoice.

Production incident response

Replay specific traces and create alerts for failing requests or unexpected behavior.

Traces

Inspect prompts, responses, retries, tool calls, latency, token usage, and failures in one timeline. Filter by tag, user, model, or status. 14-day retention with 4ms overhead via async batching.

Workflow tracing

Follow multi-step executions across agents, tools, and providers. Parent and child spans are ordered, showing the code path at a glance.

Cost breakdown

Track spend by model, provider, project, or request. See p50/p95 latency next to cost so regressions don’t surprise you on the invoice.

Waterfall graph

Visualize the full execution timeline with duration, cost, and span relationships—LLM calls, tool calls, and root spans.

Replay and alerts

Replay individual traces and create alerts for specific conditions (e.g., failures, cost spikes).

Provider-agnostic instrumentation

Works with any LLM provider or orchestration framework. Create traces and spans in a few lines of code.

Raw spans and logs

Access raw span data and logs for deep debugging, including status, model calls, and timestamps.