For Early-stage AI-native startups

Startups burn 10–30% of their runway on AI. AICosts.ai makes that number legible.

0–30%
Of startup runway spent on AI (typical)
< 0 min
To connect every major provider
0
Lines of code changed in production
0%
Typical spend reduction after 60 days

Pain points we solve

Problem: Five AI invoices per month, each in a different format, reconciled in a Google Sheet at 2 AM before the investor update.

Solution: Connect each provider once (read-only). AICosts.ai normalizes OpenAI, Anthropic, Gemini, Bedrock, Pinecone, and more into one daily-updated view.

Problem: A prompt template change 10×'d the bill overnight. The founder noticed at the next billing cycle.

Solution: Per-provider and per-model anomaly alerts fire the same day. A 3× spike on Claude Opus pings the owner in Slack or email immediately.

Problem: The AI feature that 'drives retention' has no unit-economics number attached to it.

Solution: Tag usage at the request level (customer_id, feature, experiment). AICosts.ai surfaces cost-per-customer and cost-per-feature rollups so the gross-margin question gets answered.

Problem: A YC app asked 'what's your AI gross margin?' and the answer was 'we'll get back to you.'

Solution: Monthly export of normalized usage ties directly into the finance model. Answer is one filter away, not a three-day fire drill.

What you get

Zero production impact

Read-only aggregation — no SDK swap, no proxy, no latency added to your hot path.

All the providers you already use

OpenAI, Anthropic, Google Gemini, AWS Bedrock, Azure OpenAI, Vertex AI, Cohere, Fireworks, Groq, Hugging Face, Pinecone, RunwayML, and 40+ more.

Alert budgets at the model level

Set a monthly cap on Claude Opus, GPT-4o, and Gemini 1.5 Pro independently — not a single global number that hides the actual offender.

CSV/JSON export to your finance tools

Drop the normalized monthly export into your finance workbook, Ramp, Mercury, or QBO reconciliation — no glue code.

Customer story

Seed-stage AI agents startup, 8-person team

Challenge: Spending ~$18k/month across OpenAI, Anthropic, Pinecone, and Tavily. Co-founders reconciled invoices manually. A retry loop in a nightly agent pipeline 4×'d the Anthropic bill over a single weekend before anyone noticed.

Solution: Connected all four providers to AICosts.ai in ~10 minutes total. Set per-provider budgets at 120% of trailing 30-day spend. Configured Slack alerts on 2× daily-spend anomalies.

Results:
  • Retry-loop incident detected and patched within 4 hours on the next recurrence.
  • Engineering lead pulled cost-per-experiment numbers directly into the investor update — no spreadsheet.
  • Moved 40% of non-critical agent traffic from Claude Opus to Sonnet after seeing per-model spend share; saved ~$3.2k/month.

Frequently Asked Questions

We're pre-seed. Is this overkill?+

Probably yes at $500/month in AI spend. Worth it around $3k–$5k/month when the mix crosses 3+ providers and reconciliation becomes a real hour of someone's week.

Does connecting AICosts.ai give it access to our prompts?+

No. We read usage metadata (tokens, requests, dollars, model, timestamp) from each provider's billing API. Prompts and completions never leave the provider.

What if we switch providers later?+

You keep your historical data. Adding or removing a provider doesn't affect existing records. The normalized schema means your dashboard is provider-agnostic — a migration is just a new connection.

Can we tag spend by customer to get gross-margin numbers?+

Yes, as long as your application passes an identifier (customer_id, workspace_id) through the provider SDK's metadata field. OpenAI's usage_metadata, Anthropic's custom headers, and Bedrock's request tags all flow through into the dashboard.

Ready to see your AI spend clearly?

Connect your providers in under 15 minutes. Free tier available.

Start tracking your AI spend

Free tier available. Read-only ingestion. No changes to production.