You own the metal. You built the fleet. But your buyers don't want a raw GPU — they want tokens, agents, and an API their developers recognise. ARK shards across your mixed fleet — any GPU, any generation — and turns it into a managed, multi-tenant inference product you can list, meter, and resell.
The market moved. Teams shopping for AI capacity in 2026 aren't comparing H100 hours — they're comparing tokens, latency, and agent primitives. Neoclouds that only sell GPUs are selling yesterday's unit.
It's a product team, a data team, an agent team. They want an OpenAI-compatible endpoint, not a bare-metal provisioning portal. If you can't give them one, they buy from someone who can.
A GPU renting at 30% utilisation is losing to one renting at 85%. Multi-tenant inference, not single-tenant IaaS, is what gets you there. You need the platform layer.
Schedulers, routers, quantisation pipelines, an OpenAI-compatible gateway, observability, billing — that's a platform company, not a feature. ARK is that platform, packaged.
ARK deploys on top of your existing fleet and turns it into a managed inference layer your customers hit through a standard API — without replatforming, rewiring, or refreshing hardware.
One fleet, many customers, session-level isolation. Utilisation goes up, cost-per-token goes down, and nobody shares KV with a neighbour.
Mix GPU generations and vendors in one pool. No NVLink, no InfiniBand — standard Ethernet is enough. Your older silicon keeps earning.
Customers point at a URL and get a familiar SDK surface. Zero integration tax — existing agents and frameworks just work against your cloud.
Token accounting per tenant per model, clean invoicing, usage caps, rate limits. Plug it into your existing billing stack or use ours.
Every number here is a reason your economics improve when the platform on top is ARK rather than something you glued together with open-source parts.
Your customers should pick ARK for what it does, not what it costs them per request. We license ARK by the GPUs it runs on — your commercial model on top is yours to run. No consumption surcharge. No margin erosion.
License scales with fleet size. Support scales with footprint. Add-ons are optional and priced the same way everything else is: per GPU, per month, predictable.
Pay for ARK by the size of the fleet it's deployed on. Your pricing to your customers is decoupled from ours — meter however you like, or don't.
Standard (<10 GPUs), Premium (10–50), Enterprise (50+). Determined by license count, not upsold. No feature gating between tiers.
Vision, speech, and extended model catalogues at fixed per-GPU pricing. Turn them on per deployment — not per user, not per token.
When your sales team walks into a regulated enterprise deal, ARK brings technical depth, compliance posture, and reference architectures to the table.
We've run this motion with operators at different scales. The path is well-defined: we bring the runtime, the reference architecture, and the integrator playbook; you bring the fleet and the buyers.
We map your fleet (generations, topology, networking, utilisation) against ARK's reference patterns. Output: a deployment plan and a commercial shape.
ARK's runtime is deployed on a carved-out slice of your fleet. Benchmarks run against your real hardware, with your models, on your network.
API endpoints, tenancy, metering, branding, support handoff. The platform becomes a product your sales team can quote against.
Joint design partners, joint enterprise pursuits, shared collateral. We keep iterating on the runtime; you keep selling the outcome.
Tell us the shape of your fleet and the buyers you want to land. We'll show you how to light ARK up on top of it — and what the first three customers probably look like.