AI cost monitoring, run like a budget — not a surprise.
Review connected company AI accounts in one place. Verify billing coverage, explain a spend change, and give the next review an owner.
- Read-only access
- 14-day free trial
- No credit card required
- 5 min
- setup, per provider
- Up to 90 days
- available history
- Same-day
- anomaly alerts
Daily spend by provider
$24,321 total
Use your trial to explain one business AI spend change.
Start with a company account you can administer and one spend question your team needs to answer. During the 14-day free trial, check source coverage before relying on a combined total. No credit card required.
OpenAI and Anthropic API
Organisation billing access is required. Check the provider setup guide for Admin API credentials and the fields returned by your account.
Read setup and coverage requirementsClaude tool usage
OpenTelemetry measures usage and estimated API-equivalent cost from setup onward. It does not report Pro, Max or Team subscription allowances.
Read setup and coverage requirementsCursor
A team admin needs access to the usage API. Returned events and initial history depend on API availability; usage is not a complete subscription invoice.
Read setup and coverage requirementsGrok (xAI)
A Management API key and Team ID connect daily billed USD. Model labels come from billing descriptions; this connection does not supply input/output token counts or individual user attribution.
Read setup and coverage requirements
01
Verify account and data coverage
Confirm the connected organisation, last successful sync, available history and whether each source reports billed cost or an estimate. Compare a matching date range with the provider console.
02
Explain one spend change
Compare two complete periods and identify the provider or available model breakdown driving the change. Use application logs for feature or customer context that the provider does not return.
03
Give the next review a named owner
Agree who investigates the change and what action they will take. Check plan eligibility before adding a budget or notification, then review whether the trial saved useful work.
Alerts notify an owner; they do not enforce provider spending limits.
See what is driving AI spend.
Every model you run, in one lens.
Usage by base model, project and user, in tokens and in API-equivalent value. Estimated and billed usage stay separate, so the numbers never double-count and never pretend to be your invoice.
Business plan
How it worksCatch the spike the day it starts.
StackSpend learns what normal looks like per provider, account and service, then flags the day something breaks pattern, with a severity and an owner. Each one carries a lifecycle, so it gets closed.
How it worksOne message each morning. Nobody opens a billing portal.
Team plan and above
How it worksProduct examples are illustrative. Usage estimates and provider-reported costs are separate measures; availability varies by connected source.
Explore the model viewWhy is this spend hard to control?
- AI bills scale with usage. OpenAI, Anthropic, Claude, Cursor—each has its own pricing model and dashboard. Token costs are hard to predict. By the time the invoice arrives, the damage is done.
- Fragmented visibility. You know OpenAI spend. You know Anthropic spend. You might not know Cursor spend. You definitely don't know the total until you add up multiple dashboards.
- No early warning. API costs can spike in a day—a bug, a launch, or a traffic surge. Without daily monitoring, you find out when the bill arrives.
Know what you are connecting.
The coverage
- StackSpend connects to OpenAI, Anthropic, Claude, Cursor, Hugging Face, and Grok (xAI) via billing APIs and usage ingest. One view shows total AI spend and breakdown by provider and model.
- Daily spend alerts in Slack or email. Eligible anomaly alerts use available billing data and successful syncs — with webhooks to push anomaly.created to your systems. Pace-to-forecast tells you where the month will end.
- Compare available model dimensions across connected providers. Use your application logs for request-level feature and customer context.
- For teams searching for AI cost observability, the goal is simple: know which provider, model, feature, or workflow moved spend before the invoice arrives.
The source
Billing and usage from your connected providers. Credential types and permission controls vary by provider.
Provider connection guidesThe limits
Provider reporting and scheduled sync determine freshness. The initial backfill requests up to 90 days of available data. Alerts notify your team; they do not block requests or enforce a spending cap.
What we track
- OpenAI (Organisation ID + Admin API key)
- Anthropic (Admin API key)
- Claude Code (OpenTelemetry — token-based estimate)
- Cursor (Admin API)
- Hugging Face (Endpoints, Spaces, Jobs)
- Grok (xAI Management API)
- Model-level breakdown where supplied by the connection
- Daily spend and forecasts
Who is this for?
- Product and engineering teams running multiple AI providers who need one view instead of logging into OpenAI, Anthropic, Claude, and Cursor separately.
- Teams building AI-powered features who need to track model cost as the product scales — before token spend becomes a COGS problem.
- Finance and CTOs who need a daily signal on AI spend and a forecast before the billing cycle closes.
StackSpend alongside native billing tools.
Native tools provide provider-specific reporting and controls. StackSpend adds a shared monitoring workflow across connected sources.
OpenAI usage page, Anthropic console, Cursor admin, per-provider dashboards
- Each provider has its own dashboard — there is no unified total
- Providers expose usage and cost data during the billing period; each has its own reporting and alert setup
- No cross-provider anomaly detection or forecasting
- Model-level costs are visible per provider but never aggregated
StackSpend
- Connected AI providers in one dashboard; check the source measures before combining totals
- Daily spend signal across every connected provider
- Anomaly detection catches spikes across OpenAI, Anthropic, Claude, Cursor, and Grok (xAI) together
- Available model-level breakdowns across providers in one view
Live from the price engine
AI spend management starts with a moving market
| Date | Provider | Model | Change |
|---|---|---|---|
| 2026-10-14 | together_ai | moonshotai/Kimi-K3 | price changed (output $13.50 → $15.00/MTok) |
| 2026-10-14 | together_ai | Qwen/Qwen3.7-Max | price changed (output $7.50 → $4.50/MTok) |
| 2026-10-13 | together_ai | together/Tev1-4B-experimental | price changed |
| 2026-10-13 | perplexity | pplx-decider-v1-27b | price changed (input $0.04 → $0.02/MTok) |
| 2026-10-10 | together_ai | Qwen/Qwen3.7-Max | price changed (output $4.50 → $7.50/MTok) |
| 2026-10-08 | anthropic | claude-sonnet-5-5 | price changed |
Tracking 1147 priced models. Latest change: 2026-10-14. Source: the open LLM price dataset (CC BY 4.0) — the same engine behind the LLM API pricing index.
What do you get when you connect?
- Source coverage
- Reported billing and usage-derived estimates are checked separately.
- Access
- Provider-specific billing or telemetry credentials; use minimum permissions.
- Trial outcome
- One explained spend change and a named review owner.
Check the details before connecting.
Review connection permissions
Read the provider setup guides before sharing credentials.
Provider setup guidesSee the security details
How credentials, tenant isolation and data handling work.
Security and data handlingTalk to the team
Ask about your stack or requirements before connecting.
Contact StackSpendAbout Andrew DayAI cost monitoring, answered
What causes AI / LLM Cost Monitoring costs to spike?
- A new feature ships using GPT-4 when GPT-4o-mini would handle the task at a fraction of the cost
- A prompt change increases average token count by 40% and nobody notices until the invoice
- Usage scales 5× during a product launch but no one is watching the AI billing dashboard
- Embeddings are generated on every search query instead of cached, driving hidden volume
What is StackSpend for AI cost monitoring?
StackSpend brings connected AI and cloud billing sources into one spend view, with model and user breakdowns where available, team budgets, forecasts and anomaly alerts. It helps engineering and finance teams monitor the month before the invoice arrives. Provider reporting and sync determine freshness; alerts do not enforce a spending cap.
How do I monitor cloud spending for AI workloads?
Tag or group the cloud resources that serve AI workloads, such as GPU instances, managed model endpoints and vector databases, then watch them as their own daily line next to the API and tool spend they drive. StackSpend reads cloud billing from AWS, GCP and Azure and AI usage from OpenAI, Anthropic, Claude tools and Cursor, so the GPU bill and the token bill for the same product appear together, with one baseline and one alert.
What is AI cost monitoring?
AI cost monitoring tracks spending on AI API providers, coding tools and cloud AI services so teams can review changes and forecast costs. StackSpend brings connected sources into one view; source coverage and billing definitions still need to be checked.
Who is StackSpend AI monitoring for?
Engineering and finance teams managing company AI accounts, especially across multiple providers. Start with a business spend question and an administrator who can connect the relevant account. Personal subscription allowance tracking is a different requirement.
Can I monitor AI usage and cost together?
Where a connection supplies usage fields, they can help explain spend. Coverage varies: Grok currently supplies daily billed USD, while Claude tool telemetry supplies token usage and estimated API-equivalent cost. Do not treat all sources as token-level billing records.
Can I attribute AI spend to every feature or customer?
Provider and available model detail can narrow an investigation. Feature, customer and workload ownership usually require metadata from your own application or gateway. Connecting a billing account does not automatically discover all company AI use or supply request-level customer attribution.
How is this different from native provider dashboards?
Native dashboards are useful for checking an individual provider and reconciling its bill. StackSpend adds a combined review workflow across connected providers, with budgets, forecasts and alerts where eligible. A native dashboard may be enough if you only need one provider total.
How much history loads and how quickly can I start?
Setup and first-sync timing depend on credentials and the provider API. History varies by source; Claude telemetry starts at setup and Cursor depends on returned API events. Check the last sync and available dates before comparing periods. There is no universal instant 90-day backfill.
Do alerts enforce AI spending limits?
No. Alerts notify an owner; they do not stop inference or enforce a provider spending cap. Check pricing for budget and notification feature availability, and configure provider-side controls separately where needed.
What should a successful trial prove?
A useful trial verifies the right business account and data coverage, explains one spend change using available fields, and gives the next review a named owner. Compare the work saved with your current process before choosing a paid plan.
For the current provider catalogue, see supported integrations.
Tomorrow morning: one number, in Slack.
Connect your providers today and follow spend, budgets and alerts in one place. Review provider permissions before connecting.