Cut your AI bill
Reduce AI costs by up to 70-80%, with the same quality
Most AI bills are full of waste nobody can see on the invoice: agents resending long histories, a top model answering easy questions, the same context paid for again and again, and work that could wait running at full price. We sit with your team, find where your money goes, and build a proxy that cuts it without hurting the answers. How much you save depends on your workload. The free bill review tells you your number before you commit.
Where your AI money goes, and what we change
Illustrative example, not a customer result
A 20-developer team with a $4,000 monthly coding-agent bill, worked through on public prices. Each step works on what is left after the one before.
Start: 20 developers on Claude Opus 5.5 at $200 each, the middle of Anthropic's published $150 to $250 a month
Fewer tokens: history and context trimmed 20 percent, answers 10 percent shorter. Saves $723
Never pay twice: 30 percent of cache writes were avoidable rebuilds, now read at $0.20 instead of $5 per million tokens. Saves $420
Lower price per token: 35 percent stays on Opus 5.5, 40 percent moves to Sonnet 5.5 (half price), 25 percent to Haiku 5.5 (1/40). Saves $1,261
Batch: 10 percent of what is left can wait and runs at half price. Saves $80. In total, about 62 percent lower
how the example works
The maths behind the example, and why your number will differ
This is an illustrative example, not a customer result. It uses Anthropic's published prices for Claude Opus 5.5, Sonnet 5.5 and Haiku 5.5 (October 2026) and the token mix of Anthropic's own sample Claude Code session. The shares in each step are our assumptions. The free bill review replaces them with your measured usage.
Where the $4,000 goes
Scaled from Anthropic's sample session, the month is about 364 million tokens of cache writes ($1,822 at $5 per million), 6,851 million tokens of cache reads ($1,370 at $0.20), 38.6 million output tokens ($773 at $20) and 8.7 million fresh input tokens ($35 at $4). Context, not answers, is most of the bill.
Why this example lands at 62 percent
It uses moderate shares on purpose. Workloads with broken caching, more easy traffic or more work that can wait can go further, up to 70-80%. Teams that already use cheaper models, or have little repeated context, save less. Your mix decides it.
What it does not include
The savings are gross: before our fee and before any time your team spends on the pilot. Prices are the providers' list prices on the day we checked them, and they change. Quality is the condition for every step: a rule only counts if the answers stay as good, which we test on your own work.
Price gap per token, Claude Opus 5.5 vs Haiku 5.5, prompts up to 100k tokens (Anthropic pricing, Oct 2026)
Off the input price for cache reads on Opus 5.5 and Sonnet 5.5 (Anthropic pricing)
Off input and output on batch work (Anthropic and OpenAI pricing pages)
Works with the harness your team already runs
Get your own number, not an example
Send us one month of usage exports, or tell us your tools, models and rough monthly spend. We show you where your money leaks, what we would change and the saving we expect. Free, and you decide after.
