For engineering teams

Cost regressions hide in deploys.
See them the same day.

LLM Cost Tracker gives engineering teams real-time deploy deltas, prompt version comparison, and wasted spend detection — so you catch regressions the day they ship, not the day the bill arrives.

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Tag by prompt version

Track Wasted Spend

Latency Tracking

The problem

LLM costs are an
operational problem.

Three things that make it hard to ship AI features without cost surprises.

Problem 01

Deploy regressions are invisible until too late

You ship a prompt change on Wednesday. Token counts go up 40%. By Friday the cost spike shows up in Slack. You spend the weekend reverting. Without per-deploy cost data, every ship is a gamble.

Problem 02

Wasted spend on errors and retries

Calls that time out, return empty output, or get retried three times before succeeding — each one costs real money. Without a call log you can't see them. They're invisible line items that accumulate quietly every day.

Problem 03

No way to compare prompt versions

You rewrote the system prompt to improve output quality. Did it get more expensive? By how much? Input tokens, output tokens, latency — without version-tagged data you're guessing whether the change was worth it.

Deploy deltas

Know the cost impact
of every deploy — same day.

Tag your deploys with a promptVersion — a git SHA, a label, anything. The dashboard shows avg cost per call, input tokens, output tokens, and latency for each version side by side.

If cost goes up after a ship you'll see it in the version comparison before the next standup — not when finance asks questions at month end.

deploy.yml

# Set on deploy — auto-tags every call
DEPLOY_SHA=$(git rev-parse --short HEAD)

# In your call site
trackedCall(({
...
promptVersion: process.env.DEPLOY_SHA,
})

Prompt version comparison · search

VersionAvg costInput tokOutput tokLatency

a3f2c1dcurrent+38%

$0.08218,4201,2401,840ms

b9e4d2a

$0.05912,1009801,420ms

c1a8f3b

$0.06112,8401,0101,510ms

a3f2c1d costs 38% more per call than the previous version — input tokens jumped from 12,100 to 18,420. Likely a context window change in the system prompt.

Call log · search · today$84 wasted

ModelTokensCostStatus

claude-sonnet-4-618,441$0.111ok

claude-sonnet-4-622,100$0.133no output

claude-sonnet-4-619,840$0.119no output

claude-haiku-4-53,200$0.004ok

claude-sonnet-4-621,200$0.127timeout

claude-sonnet-4-618,900$0.114ok

2 no-output calls + 1 timeout = $0.373 wasted in this sample alone. At this call volume that's ~$84/day burning silently.

Wasted spend

Every failed call
still costs money.
See exactly which ones.

Calls that return zero output tokens — timeouts, errors, empty responses — are flagged automatically in the call log. You can see them the same day they happen, not when you audit your API bill.

In RAG applications, retry storms are especially costly — a single bad query can trigger three or four full-context calls before failing. The call log surfaces the pattern so you can fix the root cause.

No outputZero output tokens — the model returned nothing

TimeoutCall initiated but never completed

RetryMultiple calls in rapid succession for the same query

Full observability

Everything you'd want to know
about an LLM call. All of it.

Cost by group

Break your bill down by feature — search, summarize, chat, classify. See which one is driving costs and by how much.

Cost by user

Rank internal users or customers by spend. Spot the outliers before they become a problem.

Latency tracking

Wall-clock ms on every call. See avg latency per group and correlate slowdowns with prompt changes or model swaps.

Prompt version deltas

Tag deploys with a git SHA. Compare cost, tokens, and latency across any two versions side by side.

Wasted spend detection

No-output calls, timeouts, and retry patterns flagged automatically. Know your real effective cost per successful call.

Real-time call feed

Every call as it happens. Model, tokens, cost, latency, status. The ground truth for everything the dashboard aggregates.

Get started

Catch the next cost regression before standup.

Free tier. One import. Deploy delta data flowing in 5 minutes.

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Cost regressions hide in deploys.See them the same day.

LLM costs are anoperational problem.

Know the cost impactof every deploy — same day.

Every failed callstill costs money.See exactly which ones.