Auto Models

Don’t send a professor to fetch the coffee.

Every time AI thinks, it costs money. Auto Models use a small, fast model for routine work and reserve the powerful model for genuinely hard reasoning. That is why an Auto is affordable to run at enterprise scale.

~60% fewer tokens per process Right-sized AI for each step Runs on your own AI contracts
Live model routing
New business step enters the Auto
RouterChecks the task and chooses the cheapest capable model.
Small modelFast checks, classification, extraction.
SpecialistRepeatable business reasoning.
ExpertHard judgement only when needed.
~60%fewer tokens than sending every step to the largest model
The problem

AI bills grow when every step uses the largest brain.

Many AI systems answer every step of a process with the largest available model. A fifty-step workflow pays top rates fifty times. Supervity calls this pattern tokenmaxing — impressive in a demo, expensive in production.

Tokenmaxing

Every routine step gets treated like frontier-level reasoning. The cost curve rises with every task, workflow, user, and system.

Cost grows step by step

Auto Models

The large model stays available, but it is not the default. Routine work flows through smaller and specialist models first.

Right
brain
Smallfast
Tunedroutine
Largereserve
The Supervity way

Match the brain to the task.

An Auto routes each step to the cheapest capable model. Three tiers do the work, with the Auto Graph supplying only the context each step needs.

Small, fast model

Looks at each step and decides how to handle it. Cheap, quick, and the reason the expensive model is rarely needed.

High volume · low cost
Specialist model

Handles routine reasoning specialised to your processes. It carries most of the load at a fraction of the cost.

Most business reasoning
Large model in reserve

Called only for genuinely hard reasoning, using the customer’s own AI contract. Powerful when needed, not on every step.

Used selectively
How the work moves

Lower cost per step. Millions of steps.

Enterprise work is not one prompt. It is continuous, repetitive, audited work across systems — and the savings compound with every routed step.

1

Business work arrives

An invoice, ticket, request, reconciliation file, lead list, contract, or email enters the Auto.

2

The right model is chosen

The Auto Graph supplies relevant context and Auto Models route each step to the lowest-cost capable model.

3

The action is completed

The Auto returns a decision, draft, update, validation, exception, or system action with a traceable record.

Cost comparison

Not all AI work deserves frontier-model pricing.

Auto Models keep the expensive model available without making it the default for every action.

Traditional AI routing

Extraction
Policy check
Exception
Reliable, but expensive when repeated thousands or millions of times because the largest model is used again and again.

Auto Models routing

Extraction
Policy check
Exception
Small models handle predictable steps, specialist models handle repeatable reasoning, and the expert model is reserved for ambiguity.
Connected economics

The same economics power AIshore.

When an Auto is inexpensive to run, Supervity can replace outsourcing contracts priced to headcount and still improve the operating margin.

The savings are real, and they compound.

Lower cost per step, multiplied across millions of steps, is what lets an Auto run entire operations for less than the team that used to do it — while keeping humans in control.

AIshore
margin
Lower token cost
Fewer handoffs
Continuous work
Audit-ready actions
Model your savings

See what token savings could mean for your process.

Compare today’s approach with moving to Autos, or run a three-week AutoPilot to see the economics in production.