Agents retry. Budgets shouldn't.
Control the cost of tool calls, retries, and multi-step workflows before they compound.
- 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.
Price the tools that have no billing API.
Claude Code, Cowork and Office agents emit OpenTelemetry usage straight to a StackSpend endpoint — nothing to install, no credentials stored. Usage is priced per model, user and session as a token-based estimate, and labelled as one.
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 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?
- Agents create unpredictable cost through retries, loops, tool calls, and multi-step workflows.
- A single runaway loop can multiply token volume 10x overnight.
- Native dashboards show neither cost-per-task nor the request pattern behind a spike.
Know what you are connecting.
The workflow
- 01
StackSpend monitors agent-driven spend by provider, model, and workflow.
- 02
Anomaly detection flags request-volume and cost-per-task spikes the day they start.
- 03
Daily signals and webhooks route runaway-agent events to the owner.
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
- Spend by provider, model, and workflow
- Request volume and cost-per-task
- Anomaly alerts on loops and retries
- Daily signals and webhooks
- 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.
Provider usage dashboards
- No cost-per-task or workflow view
- No alert on request-pattern spikes
- Retries and loops invisible until the bill
- No webhook for runaway-agent events
StackSpend
- Spend by workflow with cost-per-task
- Anomaly alerts on loops and retries
- Same-day signal on runaway agents
- Webhook routing to the owner
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 Agent Cost Control, answered
When is this workflow useful?
- A runaway agent loop sends 10x normal token volume
- Retries multiply requests per task
- A multi-step workflow scales cost unpredictably
- Tool calls add cost no one is tracking
How does StackSpend handle AI Agent Cost Control?
AI agent cost control means monitoring and governing the spend created by agentic systems — tool calls, retries, loops, and multi-step workflows that multiply requests unpredictably. StackSpend tracks the financial side of agents across providers and alerts the day request volume or cost-per-task spikes, so runaway loops are caught early.
What is AI agent cost control?
AI agent cost control is monitoring and governing the spend created by agentic systems — tool calls, retries, loops, and multi-step workflows that multiply requests unpredictably — so runaway cost is caught early.
How does StackSpend catch a runaway agent?
It tracks spend by provider, model, and workflow and fires same-day anomaly alerts when request volume or cost-per-task spikes — so a loop sending 10x normal volume is flagged the day it starts.
Why are agents hard to budget for?
Agentic workflows create variable, hard-to-predict request patterns through retries, loops, and tool calls, so cost can move far faster than a fixed budget anticipates.
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.