AI spend visibility for product and operations teams

LLM API Cost Audit

Know whether your LLM API bill is healthy usage growth, margin leakage, or avoidable technical waste.

Book a 20-minute fit call See where it applies

The API bill is becoming a business question.

When LLM usage scales, the real question is which products, customers, workflows, or teams are creating cost, and what is commercially worth doing about it.

For AI product companies

Understand LLM COGS by feature, endpoint, customer-facing task, workflow, or account so pricing and gross margin decisions have real cost data behind them.

where AI usage is helping or hurting margin
which customers, tasks, or features are expensive relative to pricing
where optimization could reduce COGS without damaging quality

For internal AI and operations teams

Control API spend from agents, scheduled jobs, automations, RAG flows, retries, tool loops, and API keys with unclear ownership.

which workflows or teams are driving operating cost
where retries, agents, or long-context jobs may be inflating spend
where budget ownership, limits, routing, or redesign may be needed

Get a clear readout of where LLM API spend is going.

A fixed-scope analysis using provider exports and token/request signals, built for teams that need to understand the bill before committing engineering time to optimization.

Spend concentration Find where the bill is concentrated before guessing what to optimize.

→

provider model project API key service tier time period

Cost driver signals Separate normal usage growth from patterns that may deserve investigation.

→

input/output token profile cached token signal long-context signals model mix service tier usage batch vs standard time-based concentration

If the signal is worth pursuing

The diagnostic can lead into deeper mapping or implementation work, but only where the evidence supports it.

Map spend to real work Connect API usage to business context so cost can be understood at the level that matters.

products endpoints customers workflows agents teams accounts

Prioritize savings opportunities Rank what is worth acting on by impact, confidence, quality risk, and engineering effort.

savings potential confidence quality risk engineering effort business impact owner

Implement targeted fixes Turn high-confidence findings into measured cost reductions without guessing.

model routing context reduction caching output controls batch migration retry fixes

See whether there is enough signal to audit.

In 20 minutes, we can talk through your API usage, what visibility you have today, and whether a cost diagnostic would be useful.

Book a fit call