Diagnosis before promise
We measure your real spend and its composition first. Only then do we say what can be saved — using your numbers, not sector averages.
Pay less for the same AI
e-ficient reduces AI model spend for companies already running artificial intelligence, without switching providers and without migrating your application.
Audit in 72 hours · Free with a three-month plan · Savings verified before you pay
How much you could save
Move the slider to your monthly AI spend and see the estimated saving range and the tier that would apply.
1.000 € 30.000 €
Estimated monthly saving 2.400 – 4.200 €
Your tier Growth · 990 €
Net monthly saving 1.410 – 3.210 €
Estimate based on the usual 30–60% range. Your actual figure is confirmed in the audit, before you commit to anything.
Not your moment yet — but it will be
Below €2,000 a month the service does not pay for itself, and we would rather tell you. We are working on a plan for smaller volumes: leave us your email and we will let you know when it is ready.
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Your case deserves a conversation
Above €18,000 a month the saving runs into tens of thousands a year and the approach stops being standard. Scope, integrations and terms are defined with you.
Let us talk about your caseWhy it works
No application migration
Integration requires no application migration and no provider switch.
Verifiable savings every month
Each month you receive your invoice compared with and without e-ficient. If the saving is not in the report, it does not exist.
Who it is for
Companies already running AI in production and watching the invoice grow without clear control: finance leadership that needs predictability, technology leadership that does not want to slow delivery, and procurement that needs to justify the spend.
Use case
A support assistant growing faster than its budget
A company answers its customers with an assistant built on language models. It works, usage grows every month, and the bill climbs without anyone being able to say which part comes from what. We start by measuring: which kinds of requests drive the spend, which model each one is being resolved with, and which would be resolved just as well another way. From there we adjust the routing between models and reuse what repeats. The assistant answers the same, the engineering team does not rebuild the application, and the bill becomes something you can explain and budget for.
What we do not do
We do not work below €2,000 a month
If your AI spend is under that volume, the service does not pay for itself and we will say so in the audit. We would rather turn you down than charge you for something that does not add up.
We do not save money by degrading quality
Lowering response quality is not saving: it moves the cost elsewhere. We measure quality before we start and monitor it afterwards. If a saving required degrading it, we do not apply it.
We do not promise figures we have not measured
The 30–60% range describes what we usually see, not a promise for your case. Your specific figure comes out of the audit, from your own data, before you commit to anything.