Small language models · custom-built & shipped

Stop renting intelligence
by the token.

Own a small model that does your job — cheaper, faster, private, and forever. Train big once to teach it; deploy small to run it. Lower operating cost, higher close rate.

The problem

The frontier bill never stops growing.

You rent, you don’t own

Every answer is a metered API call. Scale your traffic and the invoice scales with it — forever.

You’re exposed

Your prompts and customer data leave your building. The vendor can change the model, the price, or the terms.

It’s often overkill

You’re paying frontier prices for a narrow, repetitive task a small model could own outright.

The model

Train big once. Deploy small forever.

Train big — once

A frontier model earns its keep one time: it defines the task, generates and curates the training data, and sets the quality bar. You pay the big model to teach — not to run.

Deploy small — forever

A fine-tuned small model hits that bar on your narrow job, then runs local, offline, and fast — at near-zero cost per call. You own the weights. The recurring bill stops.

The proof — measured, not promised

Numbers from our own work.

75 → 95%

accuracy — a 4B we fine-tuned, one short run

30× smaller

a tuned 4B matching models 30× its size

15 / 15

tool-call reliability that completes the action

$0 / token

no API bill once it runs on hardware you own

See the full head-to-head and method in the research →

Why it wins

Six reasons owners choose it.

Lower OpEx

The per-token invoice that grows with your traffic becomes a one-time training cost plus cheap, owned inference.

You own the weights

The model and the data are yours. No vendor can raise your price, deprecate your model, or read your prompts.

Private by default

Runs on your hardware — even fully offline. Your proprietary and customer data never leaves the building.

Low latency

No network round-trip to a frontier API. Answers come back fast enough for real-time voice and chat.

Reliable tool calls

We select the base by measurement, so the model actually emits the clean JSON that completes an action.

No lock-in

Swap it in behind your existing interface. If you ever leave us, you keep a working, documented model.

Good for

Narrow, high-volume, or private.

Classification & routingStructured extractionOn-device agentsHigh-volume, narrow tasksPrivate / regulated dataOffline & edge deployment

How we work

Measured end to end.

  1. 1
    Select the base by measurement

    We score candidate models on your production criteria — not brand or leaderboard.

  2. 2
    Fine-tune against a held-out gate

    The tuned model must pass objective checks it never trained on, red-first, before we ship.

  3. 3
    Ship it — and tell you the edges

    You get a model you own, documented, and an honest map of where its competence ends.

Own your model.
Lower the bill. Close more.

Two ways to move: have us build and ship it, or bring us in to advise. Either way, it's measured — we show you the numbers before you commit.