Free LLM bill teardown

Stop renting AI you could own.

Move your AI off rented APIs and onto private models that run in your own cloud. Faster, cheaper, and yours. Start with a free 30-minute teardown of your LLM bill.

Free · 30 minutes · plan in 48 hours

Book your free LLM bill teardown

With a senior AI engineer, not a sales rep. Step 1 of 2.

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Next, you pick a time. Happy to sign your NDA before the call.

Your 48-hour plan shows
✓
Which AI workloads can move to private, open-weight models
✓
What you’d save in cost and speed, without losing quality
✓
A safe path to switch, with frontier models kept as a fallback
Already happening

Teams are moving specialist work to models they own

Fraud prevention

A fine-tuned Qwen3.5-9B beat Claude Opus 4.5 at catching fraud, with 12 points better recall and 55% lower latency. Training cost: under $100.

Coinbase engineering blog, Oct 2026
Visual search

Runs open-source models that perform close to frontier models at less than 10% of the cost.

Fortune, Mar 2026
Customer service

Its support agent leans on Alibaba’s open Qwen models, which CEO Brian Chesky called very good, fast and cheap.

Fortune, Oct 2025
Coding agent

Built its Composer 2 model on the open-weight Kimi K2.5, then trained it further on its own data.

VentureBeat, Mar 2026
Analytics agent

An open-weight Kimi model edged out Claude Sonnet 4.6 on its internal eval at about a third of the cost.

Amplitude engineering blog, 2026

Public examples reported by the companies and press named above. They are not Crowdlinker clients.

100+
products shipped since 2013
Strategy, design and engineering for startups and enterprise product teams, from Toronto and Barcelona.
Product teams we’ve shipped with
Shopify
NBCUniversal
FreshBooks
League
MLSE
Top Hat
How the teardown works

From your AI bill to a plan in 48 hours

1

The 30-minute call

Walk us through your AI features, the models behind them and roughly what you spend. No data export needed.

2

Our analysis

We size each workload and check which open-weight models can match it, hosted or in your own cloud.

3

Your 48-hour plan

A short written plan: what to move, to which model, expected savings, and what stays on frontier models. Yours to keep.

What happens next

1Prove it on your data. We tune an open model for your task and test it side by side with what you use today.
2Move it into your cloud. Your data stays with you, and frontier models stay on as a safety net.
3Keep getting better. We retrain and swap in stronger open models as they ship, so you’re never locked in.

Who this is for

✓CTOs and engineering leaders with AI features in production, or about to launch
✓Teams spending $5K+ a month on OpenAI, Anthropic or similar APIs
✓Anyone who needs data to stay in their own cloud, or is tired of rate limits and model retirements

Questions

Will open models be as good as Claude or GPT?

Not at everything. Frontier models still lead on hard, open-ended reasoning. But for narrow, high-volume tasks like classification, extraction, routing and support, a fine-tuned open model often matches or beats them. The plan tells you which is which.

Do we have to run our own GPUs?

No. Open models can run on hosted providers, in your own cloud account or on-prem. We recommend the simplest option that meets your cost, latency and data needs.

Why is the teardown free?

It’s how we both find out if moving is worth it. If the savings aren’t meaningful, we’ll say so, and you keep the plan.

Book a free teardown
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