⚡ Your API bill is eating your Q4 margin. Get a FREE 15-min cost teardown
Supporting AI Startups 🚀

Cut Your LLM Costsby 20% in 1 Day

  • See your monthly API overpayment
  • Find your biggest savings
  • Keep your stack unchanged
Get My Free 15-Minute API Cost Teardown
LLM bill · October$54,000$30,800
AI
−20%
{ }
tokens / request4,820→ 1,960
AI
AI
cache hit rate94%
batch −50%
our engineers + cost-analysis agents

Built for AI startups spending $10k+ a month on LLM APIs

The Real Cost Of Token Waste

DKDana K · CFO

Why did the API bill jump 41% this month? We didn't add that many customers. 😬

MRLead investor

Before the partner meeting: what's gross margin on the AI product?

Gross margin 52% ↓

Shrinking Gross Margin

Investors don't care which model you call. They care that every new customer costs more to serve, and the margin story falls apart in diligence.

Monthly API spend $46,308 +$21,420.00

Burned Runway

Every wasted token is cash out the door. The bill grows faster than revenue, and months of runway disappear into retries and resent prompts.

Search call sites
support_agent.reply()$18,600/mo
tickets.classify()$7,400/mo
chat.respond()$6,300/mo
reports.nightly()$5,800/mo

Lost Engineering Weeks

Your best engineers end up reading invoices instead of shipping. Cost work never makes the sprint, so the waste keeps compounding.

1 Day

Direct Setup

Kickoff in the morning, pull request by the evening.

20%+

Guaranteed Saving

Measured on cost per request, not vanity metrics.

No Retainers

Walk Away Anytime

You pay once, from savings we verified.

Works With Every Major Model Provider

OpenAI Anthropic Google Gemini AWS Bedrock Azure OpenAI xAI (Grok) DeepSeek Qwen Mistral AI Meta Llama Groq Perplexity Cohere Together AI Fireworks AI OpenRouter Vertex AI Ollama

+ any open-source model

From First Call To First Cut

Cost teardown
Cost Engineer
You
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Call With a Cost Engineer

A 15-minute call to look at your usage, size the waste and show exactly what we'd change. Optional if you're ready to start.

Let's Confirm a Few Details
Read-only access only. We never need write keys or raw customer data.
yourstartup.ai
$25k–$100k
OpenAI, Anthropic
⇧ Upload CSV
Connect GitHub
Support agent, ticket triage, nightly reports
DPA
Guarantee terms
Mutual NDA

Onboard and Sign the NDA

Share a usage export and read-only repo access, then sign the NDA and guarantee terms. It takes under 30 minutes.

Search your-startup workspace
your-startupThreadsMentionsChannels# apicuts-cuts# engineering# general
# apicuts-cuts
apicuts bot10:42 AM

✅ support_agent.reply() is now cached. −$8,700/mo

apicuts bot1:15 PM

✅ tickets.classify() moved to a small model. Evals 99.6%. −$6,150/mo

Sam (CTO)1:20 PM

let's go 🚀 merging after standup

apicuts bot5:30 PM

📊 Daily update: 4 fixes shipped · cost per request −38% · 0 eval regressions

Dedicated Slack, WhatsApp or Telegram Channel

Pick the app your team already uses. Your engineers and ours share one channel, and every fix, eval run and saving is posted there as it lands.

Bill Before$54,000
Bill After$30,800
Monthly Savings$23,200
Cost per request, last 30 days

Access to Your Savings Dashboard

See every call site, what we changed and what it saves, with cost per request tracked daily.

Victor, founder of apicuts

Victor

FOUNDER | INVESTOR

I know how it feels when your API bill grows faster than your revenue.

I ran B2B licensing LLM infrastructure at Atlas Scales and cut our bill from $14K to $9.8K. I kept seeing the same waste everywhere:

  • System prompts resent on every turn
  • Retry loops billing twice
  • Nightly jobs on the real-time API

That's why I built apicuts, so AI founders stop paying for tokens in excess.

Let me show you where your 20% is hiding.

Book a Call with the Founder

Frequently Asked Questions

We analyze your API usage exports and the code that makes model calls. We identify the highest-cost call sites, quantify the avoidable spend, and ship the recommended fixes as one pull request.

Typical fixes include caching, model routing, batching, prompt reduction, and output limits.

Your team reviews and merges the changes. We then compare cost per equivalent request against your baseline.

You leave with:

  • The exact call sites driving spend
  • Your estimated monthly overpayment
  • The highest-impact fixes
  • A clear recommendation on what we can ship first

No generic advice. We use your actual usage data.

Yes. They should be able to.

The problem is usually not whether they can write the code. It is finding the waste quickly, prioritizing the highest-value fixes, and validating that savings do not damage quality or latency.

We compress that work into a tested pull request.

We target one working day from kickoff to pull request.

Savings are then verified against your real usage over an agreed measurement period, typically 14 days.

No. A change that doesn't meet your quality and latency requirements doesn't ship.

We test against your existing evaluations, or help create a representative evaluation set before implementation. We track cost, latency, error rate, and output quality before and after the change.

Usually, no.

We start with usage exports, token counts, metadata, and the code that makes the calls. If logs or prompts are required, you can redact sensitive information first.

We only request the minimum access needed to do the work.

We do not require permanent storage of prompts or user content to complete the work.

Before kickoff, we document what data is accessed, where it is processed, how long it is retained, and how it is deleted.

We define the baseline before implementation.

If the approved fix does not reduce eligible cost per equivalent request by 20%, you pay nothing for the implementation and keep the code.

No.

The deliverable is a pull request in your codebase. You keep control of the implementation, providers, and infrastructure.