WeaveScope

Trace, debug, and monitor AI agents running on the BEAM.

WeaveScope shows you what happened inside every agent run. Follow model calls, tool calls, errors, latency, token usage, and cost from one trace, then monitor those signals across production.

Start free · Send your first trace

What you can do

Trace an agent run

See the complete run tree, including model calls, tool calls, inputs, outputs, errors, tokens, and cost.

Debug a failure

Find the step that failed, compare timings in the waterfall, and inspect the data recorded for that observation.

Monitor production

Track traffic, latency, errors, token usage, model cost, and tool performance over time.

How WeaveScope organizes your data

Projects keep traces for different applications or environments separate. Each project has its own API keys and retention settings.

Traces represent complete agent runs, such as one user request, background job, or graph execution.

Observations are the individual steps inside a trace. An observation can be an agent, model call, tool call, retriever, guardrail, chain, or generic span.

API keys connect telemetry to a project. Keys begin with ws_, are shown in full only once, and should be stored as secrets.

Start tracing

If your application uses Elixir, the fastest route is BeamWeaver . Configure a project API key and add trace metadata at the boundary of the operation you want to observe. BeamWeaver then exports the agent, model, and tool observations in the background.

If you use another client or an OpenTelemetry collector, send data through the Ingestion API .

Once traces arrive:

1. Use Tracing to inspect individual runs.

2. Use Monitoring to follow production trends.

3. Add model pricing if a custom model shows zero cost.