CANUS

Next development / Inference network

In development

Build the cloud.Connect the demand.

CANUS is developing one inference service across independent AI clouds. AI companies would buy the service from CANUS; participating clouds would supply agreed capacity and keep their existing customers. As demand grows, the next build can enter the CANUS programme.

In development. Expressions of interest only; the inference service is not yet available.

In ordinary words

Inference is the model at work.

Training teaches a model. It happens in long runs, in one place, before anyone uses the product.

Inference is the model doing its job: every question answered, every reply written, every image read. It happens each time a customer uses the product, all day, wherever those customers are.

Training

Teaching the model.

Long runs on a large cluster, in one place.

Once, then again when the model changes

Inference

The model doing its job.

Short bursts on GPUs that are running, reachable and near the people using them.

Every use, everywhere, all day

Inference needs GPUs that are running, reachable and close to the people using them.That is the demand the network would connect to independent clouds.

How it would work

One service.Many independent clouds.

AI companies would deal with one service. Independent clouds would supply it. CANUS would sit between them, holding the agreement and keeping every responsibility on one record. Where demand outgrows the capacity supplied, the next build enters the CANUS programme.

  1. Demand committed

Network · Demand committed

Tap a step to hold it

Demand, service delivery and expansion, connected. Every party keeps its own contracts and its own decisions.

Admission to the network

Verified first.Connected next.

Our planned network would admit GPU capacity only after independent verification and testing for the agreed AI workload. CANUS would then bring that capacity into one inference service for AI companies.

  1. Independent verification
  2. Tested for the agreed AI workload
  3. Connected to one inference service

Who supplies what

Each party brings its part.Each keeps what is its own.

AI companies

  • 01Inference demand, stated as capacity, locations and service expectations
  • 02One agreement with CANUS
  • 03Payment for the service used

What it keeps

Keeps its models, its data and its customers.

CANUS

  • 01The customer agreement and the service
  • 02Matching committed demand to committed capacity
  • 03One record of responsibilities in LARUS
  • 04The route into the programme for the next build

What it keeps

Owns no GPUs and operates no cloud.

Independent clouds

  • 01Agreed capacity, on agreed terms
  • 02Operation of their own infrastructure
  • 03Locations where the demand is

What it keeps

Keeps its infrastructure, its existing customers and its own commercial terms.

Why both sides

Demand meets the clouds that can build for it.

For AI companies

Buy inference once.Run it in many places.

  • 01One agreement, with the capacity, locations and responsibilities written down
  • 02Capacity across independent clouds, without negotiating with each one
  • 03Delivery and responsibilities kept on one record

For independent clouds

Serve new demand.Keep your cloud.

  • 01Network demand alongside your existing customers, not instead of them
  • 02Your infrastructure, your operations, your commercial terms
  • 03A route for the next build through the CANUS programme when demand grows

Participation would be agreed cloud by cloud, with capacity, locations and terms set out in writing before anything is supplied.

From demand to the next build

The commitments that could support the next buildout.

Today an independent cloud brings its next project into the CANUS programme with the demand it has found itself. The network would add a second source: inference demand CANUS has already agreed with customers. Where that demand outgrows the capacity in the network, the next build has a customer case before it starts.

  1. 01

    Commitments accumulate

    AI companies commit to agreed capacity through the service. Each commitment is recorded with its locations and its term.
  2. 02

    The gap becomes visible

    LARUS shows where committed demand exceeds the capacity participating clouds have supplied, location by location.
  3. 03

    The next build enters the programme

    A participating cloud brings its expansion into the CANUS programme: funding coordination, delivery, independent checks and the record, as for any project.
  4. 04

    New capacity joins the network

    Once delivered and checked, the new block is supplied to the network on agreed terms, and the loop begins again.

Customer commitments can support plans for more capacity. Any financing remains subject to the lender’s approval and terms.

One service. Clear responsibility.

Your AI workload.One accountable team.

We’re developing one CANUS inference service across participating AI clouds. Instead of managing several cloud relationships, an AI company would come to CANUS for the service, support and billing.

The clouds supply the agreed GPU capacity. CANUS manages the service. A qualified external firm would independently check the supplied capacity against agreed requirements.

In development. External verification arrangements are not yet in place.

Where this stands

In development.

Stage
In development
Inference service
Not yet available
Capacity
Agreed with participating clouds as the network develops; none is reserved through this page
Participating clouds
Expressions of interest being gathered
Pricing
Not yet set
External verification
Qualified external firm proposed; not yet appointed
The CANUS programme
Unchanged. The network is separate from the founding offer.

Questions

Asked before anyone signs anything.

  • For the proposed inference network, a qualified external firm would carry out the independent checks and issue its own findings. CANUS would remain responsible for its service. This keeps the seller and the independent checker separate. The external firm has not yet been appointed.

Expressions of interest

Tell us which side you are on.

Two short paths. Choose the one that fits and say what you would bring. A named person replies; nothing is committed by writing.

Choose your path

Tell us roughly what you would run, where your users are and when you would need capacity.

  • 01What you run, in a sentence
  • 02Where your users are
  • 03When you would need capacity, and roughly how much

Expressions of interest only. The inference network is in development; submitting does not reserve capacity.

The inference network

Build the cloud.Connect the demand.

One service for AI companies. Agreed capacity from independent clouds. A route for the next build through the CANUS programme. In development, and taking expressions of interest from both sides.

The CANUS programme

In development. Expressions of interest only; the inference service is not yet available.