Protect margins as AI usage scales.
Catch AI cost movement before it reaches the P&L — baselines, budgets, and same-day alerts.
- Read-only access
- 14-day free trial
- No credit card required
- 5 min
- setup, per provider
- 90 days
- available history
- Same-day
- anomaly alerts
Spend vs Budget
Forecast $61,000 this month
Spend anomaly · high severity
AWS / NAT Gateway — $891 vs $286 expected (+212%)
See the workflow in practice.
Catch 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 worksEvery dollar has an owner.
Auto-tagging rules label costs as they are ingested, matching provider, account, service and project patterns in priority order. By the time someone asks who owns the spend, the answer is already on the data — filterable and groupable in the explorer.
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 data viewWhy is this spend hard to control?
- A prompt change, model upgrade, or new customer can change gross margin overnight.
- Margin erosion is usually discovered at the monthly close, when it is already booked.
- Finance sees the P&L impact; engineering sees the usage — neither connects them in time.
Know what you are connecting.
The workflow
- 01
StackSpend ties AI spend to margin and usage so erosion is visible as it happens.
- 02
Anomaly detection flags cost movements that threaten unit economics the day they start.
- 03
Shared daily signals give engineering and finance the same early warning.
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. Available history and attribution vary by source; review the setup guide for coverage. Alerts notify your team; they do not block requests or enforce a spending cap.
What we track
- AI spend vs margin and usage
- Cost-per-customer and per-feature movement
- Anomaly alerts on margin-threatening changes
- Pace-to-forecast on AI COGS
- 90 days of history
Who is this for?
- Product and engineering teams that need model-level visibility before AI bills surprise them.
- Buyers consolidating OpenAI, Anthropic, Claude, Cursor, or open-model spend into one operating view.
- Teams that need alerts and forecasting, not just retrospective usage dashboards.
Evaluation checklist
- 01
Start a trial
Open a StackSpend workspace with no credit card required.
- 02
Connect with read-only access
Use the setup guide to connect the provider or workflow with the minimum permissions needed.
- 03
Review the first 90 days
Check history, alerts, anomalies, and forecast so you can decide whether the workflow is worth adopting.
How does StackSpend support this workflow?
Native tools provide provider-specific reporting and controls. StackSpend adds a shared monitoring workflow across connected sources.
Monthly P&L and provider dashboards
- Margin erosion seen only at close
- No link between usage and P&L impact
- No same-day alert on cost movement
- No per-customer margin view
StackSpend
- Margin movement visible as it happens
- Same-day alerts on cost that threatens margin
- Shared engineering and finance signal
- Per-customer and per-feature margin
What do you get when you connect?
- Setup time
- Most teams can connect and validate setup in about 5-10 minutes.
- Access model
- Read-only credentials only. StackSpend does not modify provider resources or billing settings.
- Signals
- Daily Slack or email updates, anomaly alerts, and budget tracking in one workflow.
- History and forecast
- Historical spend context plus pace-to-forecast so overruns are visible before month-end.
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 Margin Protection, answered
When is this workflow useful?
- A model upgrade triples cost per request
- A new enterprise customer is unprofitable at current pricing
- An agent loop erodes margin overnight
- A prompt change quietly raises COGS
How does StackSpend handle AI Margin Protection?
AI margin protection means catching the AI cost movements that erode gross margin — a model upgrade, prompt change, new customer, or agent loop — before they reach the P&L. StackSpend monitors AI spend against margin and usage in real time and alerts the day a change threatens unit economics.
What is AI margin protection?
AI margin protection is catching the AI cost movements that erode gross margin — a model upgrade, prompt change, new customer, or agent loop — before they reach the P&L, by monitoring AI spend against margin and usage in real time.
How does StackSpend protect AI margins?
It ties AI spend to margin and usage, then fires same-day anomaly alerts when a change threatens unit economics — so erosion is caught the day it starts, not at the monthly close.
What causes sudden AI margin erosion?
Common causes are a model upgrade raising cost per request, a prompt change growing tokens, an unprofitable new customer, or an agent loop multiplying calls.
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.