◈ B2B distribution

Trade orders in.
Stock out on time.
Infrastructure for less.

Distribution businesses live on volume and accuracy: price lists for thousands of accounts, orders arriving by portal, file and phone, stock that has to agree across depots. The systems behind that need to be dependable, and they need to cost less. Compute prices the same machines under the leading cloud and bills by the second.

Used by trade suppliers, B2B distributors and Fortune 500 distribution groups — and the start-ups building tools for them — for portals, ordering and stock.

30%
Under the leading cloud on CPU instances
Per-second
Billing on every machine
Zero
Minimums or commitments
One
Bill across every depot

What this looks like in practice

◆Trade ordering portals and account pricing◆EDI and order file processing◆Inventory across depots and warehouses◆Product information and catalogue management◆Invoicing, credit and account management◆Demand forecasting and replenishment◆Sales rep and field ordering apps◆Trade ordering portals and account pricing◆EDI and order file processing◆Inventory across depots and warehouses◆Product information and catalogue management◆Invoicing, credit and account management◆Demand forecasting and replenishment◆Sales rep and field ordering apps
What holds true here

Four things you stop arguing about

◆

Account pricing that holds

Price lists for every trade account kept in one place, with a record of what changed and when.

◇

Batch work, priced to the batch

Overnight order processing and replenishment runs billed by the second, on CPU instances 30% under the leading cloud.

◈

Stock that agrees

Inventory across depots held in managed databases priced 30% under the leading cloud’s managed databases, with one version of the truth.

○

One bill for the operation

Portals, databases, storage and code itemised together rather than reconciled across vendors.

The shift

Distribution economics, applied to infrastructure

Distribution businesses negotiate hard on every input. Cloud infrastructure has often been the exception — bought on list price, sized generously and rarely revisited.

The usual arrangement
  • ✕Servers running all day for batches that take an hour
  • ✕Account pricing spread across several systems
  • ✕Stock figures that disagree between depots
  • ✕Portals, data and code on separate bills
  • ✕Cloud prices nobody has compared
What replaces it
  • ✓Batch runs billed by the second, then stopped
  • ✓Account pricing held in one place with a history
  • ✓Stock held once and read everywhere
  • ✓One itemised bill for the operation
  • ✓Prices published beside the leading cloud’s own
What you can count on

Stated plainly, and qualified

30%
Under the leading cloud on CPU instances
Same specification, cheapest the leading cloud match
30%
Under the leading cloud’s managed databases
Per managed database-hour
Per-second
Billing
Overnight runs cost what they take
Published
Prices
With the leading cloud’s own beside them
Closer in

Wholesaling, specifically

A price list you can compare

Distribution businesses know their input prices to the penny. Infrastructure should be no different. Every Compute price is published with the leading cloud’s own price for the same thing beside it, so the saving is something you check rather than something you are told. That holds for a regional trade supplier and for a national distribution group.

Trade portals from git

Ordering and account portals deployed on Panel with builds priced under the leading cloud’s hosting builds.

Order files on queues

EDI and order files collected through Cloud Services queues and processed as they arrive.

Forecasting on CPUs

Replenishment and demand models run when needed and stopped after.

Support that fits

Developer, Business and Enterprise support, monthly, priced under the leading cloud’s support minimums.

Against the leading cloud

Wholesaling on Compute, against the leading cloud

4 vCPU / 8 GB server
$0.0941/hr
Leading cloud $0.1344/hr · Its cheapest machine with 4 vCPU and 16 GiB
30% less
Database
$0.0112 / database-hour
Leading cloud $0.016 / database-hour · Managed database, smallest instance
30% less
Build minutes
$0.007 / build minute
Leading cloud $0.01 / build minute · Managed hosting build minutes
30% less

Compared with the leading cloud's own published on-demand prices, US East. Every comparison.

Questions we are actually asked

Answers without the hedging

How do we check the saving?+

Every price is published with the leading cloud’s price for the same thing beside it, at /compare. For CPU instances, managed database hours, build minutes, AI inference and support plans, ours is 30% under.

Can it handle large overnight batches?+

Yes. Machines start for the batch, bill by the second and stop when it finishes.

Can we move our trade portal without downtime?+

In stages, with the existing portal still running. Nothing is cut over until you have chosen to switch.

Do we commit to a term?+

No. There are no reservations or minimums. Support plans are monthly.

Other industries

Where else this goes

AI Agents

Run agents, the tools they call and the models behind them on one platform, billed by the token and the second, for less than the same work costs on the leading cloud.

Customer Acquisition

Host the landing pages, attribution pipelines and onboarding flows that bring customers in, and spend less on the infrastructure than you would on the leading cloud.

Marketing

Run campaign sites, personalisation, content pipelines and marketing data on one platform that costs less than the leading cloud for the same machines and models.

Lead Generation

Run the forms, enrichment jobs, scoring models and routing that turn interest into leads, for less than the same infrastructure costs on the leading cloud.

Sales

Run CRMs, sales data, call analysis and AI assistants on one platform, priced under the leading cloud for the same machines, databases and models.

Creator Economy

Host creator platforms, media processing, storefronts and AI tools on infrastructure that bills by the second and costs less than the leading cloud for the same machines.

Start where it matters most

Begin with one workload. Keep what you have running. Decide whether to continue once you have seen it carry something real.

No migration required to begin. Nothing to tear down if you stop.