TOOLS
AI Cost Leak Diagnostic
You do not need perfect telemetry to start. This diagnostic uses workflow presets to estimate where AI spend is likely leaking: retrieval, retries, human review, tool calls, evaluation, or low first-pass resolution. Treat the result as a directional range, then validate it with traces and invoices.
No traces yet
Use a workflow preset and rough monthly volume.
Some telemetry
Replace assumptions with token, retry, and review data.
Audit-ready
Validate against traces, invoices, and sampled outputs.
START HERE
Use a workflow preset
Most teams do not know token counts, retry rates, or review costs on day one. Pick the closest workflow, enter rough monthly volume, then refine the advanced fields when telemetry is available.
Current monthly cost
$40,836.00
Optimized monthly cost
$23,111.00
Estimated savings
$17,725.00
Cost per resolved task
$0.56
Workflow inputs
Optimization assumptions
RESULT
43% lower projected monthly cost
This calculator is not guessing model pricing. It shows how the workflow changes when you reduce context, route simple tasks, increase cache hits, lower retries, and improve first-pass resolution.
Current range
$30,627.00 - $55,128.60
Optimized range
$17,333.25 - $31,199.85
Directional estimate. Replace assumptions with traces, invoices, and review-queue data before making procurement or staffing decisions.
Current cost breakdown
Optimized cost breakdown
What matters most here
- 50,000 monthly tasks means every retry point matters.
- Human review dominates when review rate or review minutes are high.
- Routing is only valid if the cheaper model still passes the task rubric.
- Cost per resolved task is the better operating metric than token spend.
COST OPTIMIZATION REVIEW
Want to optimize AI cost?
We can review traces, routing, retries, retrieval, human review burden, and model choices to find where spend is leaking before you scale.
METHOD
How we make this reliable without system access
We ask for workflow type and monthly volume first, because most teams know that before they know tokens.
We separate known inputs from assumptions, so the estimate is not pretending to be an invoice.
We focus on cost per resolved workflow, which captures retries, failed attempts, and review burden.
We show which cost bucket dominates instead of claiming one model switch will solve everything.
We use presets as benchmarks, then replace them with telemetry as soon as traces are available.
We do not recommend cheaper routing unless quality, safety, and escalation thresholds still pass.
We turn the calculator into an audit checklist: traces, invoices, review queues, and evaluation samples.
We use the result to prioritize a cost leak review, not as a final procurement decision.
AUDIT PATH
What makes the real number defensible
| Signal | What it proves | Typical source |
|---|---|---|
| LLM traces | Tokens, latency, retries, model routing, prompt/context size | OpenTelemetry, LangSmith, Langfuse, vendor logs |
| Application events | Task starts, completions, escalations, abandonment | Product analytics, backend logs |
| Human review data | Minutes spent, edit distance, escalation reasons | Review queues, QA tools, ticketing |
| Invoices | Actual provider, infra, vector DB, and tool/API spend | Cloud and vendor billing exports |
| Evaluation samples | Whether cheaper routing still passes quality and safety thresholds | Human review plus automated evals |