Unified AI and LLM spend visibility. Before the invoice, not after.
StackSpend tracks AI costs across OpenAI, Anthropic, Cursor, Hugging Face, and Grok in one dashboard. Token-based pricing is unpredictable — a product launch, a model change, or a prompt bug can double spend in a day. Get daily spend alerts, model-level breakdown, anomaly detection, and forecast before the billing cycle closes.
Why this spend is hard to control
AI bills scale with usage. OpenAI, Anthropic, 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.
What StackSpend shows
StackSpend connects to OpenAI, Anthropic, Cursor, Hugging Face, and Grok via their billing APIs. One view shows total AI spend and breakdown by provider and model.
Daily spend alerts in Slack or email. Anomaly detection catches spikes the day they happen — with webhooks to push anomaly.created to your systems. Pace-to-forecast tells you where the month will end.
Model-level visibility. See GPT-4 vs GPT-3.5, Claude vs Cursor. Understand what's driving cost.
For teams searching for AI cost observability, the goal is simple: know which provider, model, feature, or workflow moved spend before the invoice arrives.
What we track
Common cost triggers
Real scenarios that cause spend to spike — often silently.
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
OpenAI usage page, Anthropic console, Cursor admin, per-provider dashboards
Native tools are built for investigation. StackSpend is built for prevention.
OpenAI usage page, Anthropic console, Cursor admin, per-provider dashboards
- Each provider has its own dashboard — there is no unified total
- Billing is monthly — no daily signal, no early warning
- No cross-provider anomaly detection or forecasting
- Model-level costs are visible per provider but never aggregated
StackSpend
- All AI providers in one dashboard with a combined total
- Daily spend signal across every connected provider
- Anomaly detection catches spikes across OpenAI, Anthropic, Cursor, and Grok together
- Model-level breakdown visible across providers in one view
Who this is for
Product and engineering teams running multiple AI providers who need one view instead of logging into OpenAI, Anthropic, 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.
What you get when you connect
Most teams can connect and validate setup in about 5-10 minutes.
Read-only credentials only. StackSpend does not modify provider resources or billing settings.
Daily Slack or email updates, anomaly alerts, and budget tracking in one workflow.
Historical spend context plus pace-to-forecast so overruns are visible before month-end.
Frequently asked
What AI providers does StackSpend connect to?
How is this different from the OpenAI or Anthropic native usage dashboards?
Can I track AI costs by model?
How long does AI cost monitoring setup take?
How do I monitor API usage and costs across providers?
Start seeing your full stack spend.
Connect ai / llm cost monitoring in under 5 minutes. 90 days of history loaded automatically. Daily signals from day one.