topologist

Compute,connected.

Find the right compute. Run through one interface. Put spare capacity to work.

We’re building a compute marketplace and integration layer for developers, providers, and teams with spare capacity.

Discuss a workloadExplore our approach

Integrate once.
Unlock a world of compute.

Use one interface to prepare and run supported workloads on compatible compute. Bring capacity you already have, or connect capacity you purchase through the market.

Proposed workflow

Check before you run. Check memory, fabric, location, and runtime against the workload before execution on the selected capacity.

More work done.
Less orchestration.

Make large and recurring AI jobs reliable, even on compute you already have. We’re building AI-assisted workflows to plan, run, and recover supported jobs through to verified completion, within your execution, cost, and data limits.

  1. Plan

    Compare qualified layouts and use targeted measurements to generate a supported configuration and recovery plan.

  2. Run & recover

    Prepare data, launch, and track progress. Resume interrupted jobs from checkpoints on compatible, available compute where recovery is supported.

  3. Validate

    Check outputs against the job’s agreed success criteria and retain durable results. Surface failures that need attention.

  4. Repeat

    Reuse the plan and run evidence for recurring jobs. Recheck capacity and compatibility as the workload or infrastructure changes.

AI-assisted planning.
Grounded in execution.

Eight GPUs in one fast communication domain, or sixteen across two nodes? The answer depends on the workload and the connections between its chips.

We’re building a planner that compares supported layouts, identifies the measurement that would settle the choice, and runs a targeted test within your limits. The result informs the configuration and becomes evidence for future jobs.

Compatibility checks, approved execution policies, and your cost and data limits govern what can run and how it recovers.

Illustrative comparison
8GPUs

One fast
communication domain

16GPUs

Two nodes
with a link between them

More GPUs can add compute and communication overhead. A targeted measurement would settle the choice.

A simpler way to buy compute

One purchase.
All the way to ready.

Bring the requirements you know.
We’ll help with the rest.

  1. Define your need

    Workload, timing, and what matters to you.

  2. Compare suitable options

    Understand the fit, terms, and tradeoffs.

  3. Purchase and get ready

    Sign, complete payment, and verify delivery.

We’re building this purchase experience. Tell us what you need today.

Discuss a workload
Illustrative offer · In development
Capacity
8 × H100
Bid
$20 / group·hr
Ask
$16 / group·hr
Window
4 hours · firm

One qualified node. Rates cover all eight GPUs. Workload qualification and owner confirmation are required before allocation.

For developers & AI teams

Find qualified capacity without repeating provider searches and integrations. Use the same execution workflow for large jobs and recurring runs.

For providers

Reach compatible demand and make workload performance visible. Choose the capacity and terms you offer.

Explore the provider view

For teams with spare capacity

Reserved more compute than you need? Help shape a way to offer unused capacity to other teams, where your provider and contract allow.

Discuss spare capacity

Compute provider directory

Prices start
at the source.

Explore 72 compute providers, from GPU clouds and marketplaces to serverless platforms. Follow their pricing and documentation, and see which sources offer a price API.

Explore compute sources

23 documented price or quote APIs · Research snapshot . Listings are research references; integrations and live inventory are not implied.

Let’s connect.

Tell us what you want to run, the compute you use today, and where you’re getting stuck.

Discuss a workloadExplore the provider view