Timing, without the blind spot.
See latency and status alongside each request. Find the slow call rather than blaming the whole agent.
Agent observability
Every AI call.
Accounted for.
Follow the request from agent to provider. See its tokens, timing, owner, and catalog cost—without piecing the story together after the fact.
Powered by Caveman Platform · in private development
A total is not an explanation.
One invoice.
A thousand unanswered
questions.
Which workflow ran up the bill?Was it the model or the retries?Who owns the next fix?
01 / Open the request
The whole story.
One trace.
A model call is one part of an agent workflow. Select a step below to inspect the request path and the facts recorded along the way.
trace / support-triageIllustrative request
Step 2 of 3
Provider call
Record model, reported usage, cache tokens, status, and latency.
48–1,248 msUsage, as reported.
Record input, output, and cached tokens from the provider. Preserve the basis of the calculation.
Work, with an owner.
Group requests by workflow and agent. Missing attribution remains visible.
02 / Turn totals into answers
Start with a number.
End with a name.
Explore a sample ledger. Switch between agents and workflows, then select a request to inspect the cost behind it.
Caveman / Spend explorerInteractive example
Priced subtotal$0.71
Requests4
Unpriced1
Request cost, in orderUSD · example values
Sample records only. Actual subtotals use public-catalog prices and provider-reported usage, not your negotiated provider invoice.
03 / From traces to intelligence
The trace is a fact.
The pattern is a lead.
Investigate related work, repeated paths, and recurring failure themes. Move from one expensive request to a case worth testing.
Repeated verification
01Read
02Verify
03Read
04Verify
05Answer
The same artifact gets read and verified twice. Inspect the traces before deciding whether either check is redundant.
Illustrative pattern analysis · themes require suitable captured evidence · lexical clusters are not labeled semantic
Content-based analysis depends on your capture settings and available evidence. Semantic themes and lexical traffic clusters have different bases; the product keeps that distinction visible.
04 / Keep the accounting honest
Unlisted model—Unpriced
Missing price is not a zero-dollar call.
Unknown is not free.
An unpriced model stays unpriced. Missing catalog data never quietly becomes $0.
Workflow: repair-tests
JD
Engineering / JulesAgent: code-reviewAttribution is explicit.
Give a request an owner—or leave it marked unattributed until you know.
Run receipt
Model calls2
Tool calls3
Stop reasonCompleted
Illustrative receiptEvery number has a basis.
Keep the request record close to the calculation. Estimates and verified savings remain separate.
05 / From trace to workspace
Less dashboard
archaeology.
Open the request, inspect its timeline, and follow the work it belongs to. The record is already there when the question arrives.
Full payload visibility depends on your capture and retention settings. Request metadata and usage are distinct from captured content.
● ● ●Demo workspace
Interactive product UI · fictional sample data · Open full demo ↗
Make every token count.
Stop guessing.
Start tracing.
Connect your existing LiteLLM gateway through OpenTelemetry, or use Caveman’s gateway. Caveman Platform is in private development.