Your data. Your hardware. Your terms. ARK turns any hardware into an enterprise-ready inference platform — no rewiring, no dependencies.
Free credits on ARK Cloud — EU-hosted, no credit card, no data leaves the region. Contact sales for ARK Tailored & ARK Core.
Private, resilient, production-grade inference — sharded across any CPU or GPU, with no trade-offs on performance, scale, or compliance.
Data stays inside your borders. Deploy on-prem, inside your VPC, or fully air-gapped. No hyperscaler round-trips, no cross-border transfers, no third-party logging.
Any GPU, any vendor, any generation, pooled into one fleet. Shard whichever model fits the total VRAM and run several side by side — no config changes, no NVLink, no InfiniBand, no hardware refresh.
Add or remove GPUs live — no reloads, no maintenance windows, no mid-flight collapse. Keeps serving through individual GPU failures without dropping sessions. Platform teams manage what runs on ARK, not ARK itself.
Text, vision, audio, embeddings — running together across whatever GPU generations you run. Route each modality to the silicon that fits it best: newer cards for large-context text, older ones for OCR or audio. One runtime, one cluster, every modality.
Agent loops stay on the GPU. KV context is resident across turns, so you don’t re-pay the prefill tax on every call. Stateful by design — built for the way agents actually run, not stateless one-shot APIs retrofitted for long conversations.
OpenAI v1 / Anthropic compatible API. One base-URL change and your existing code works — no new SDKs, no rewrites, no vendor lock-in. Already running Keycloak, ELK, or Prometheus? Keep them. Swap any platform service for your own.
Engineering notes, benchmark results, and partnership news from the runtime. Full press archive in the Newsroom.
Why stateless APIs re-pay the prefill tax on every turn — and what a runtime built for agent loops actually looks like.
Read the post →How to run frontier models on older GPUs by sharding the KV cache across different memory tiers.
Read the post →The model is stateless. Your runtime shouldn't be. What statefulness actually costs — and what it saves.
Read the post →AI investment is up. Production isn’t. The bottleneck isn’t model quality — it’s infrastructure. Your team can prototype on a hyperscaler in a week, then spend 18 months trying to deploy the same thing behind your firewall.
ARK is the infrastructure layer that closes that gap. Production-grade inference that runs where your data lives, sharded across any GPU, any vendor, any mix — so your team ships AI, not scaffolding.
Your engineers ship AI features, not inference plumbing.
The same stack prototypes in the cloud and runs behind your firewall. No rewire.
Data residency, session-level isolation, audit-ready logs — built into the runtime.
Every high-risk AI system deployed in the EU must meet obligations for data governance, transparency, human oversight, and audit-ready logging. ARK is designed from the runtime up to satisfy those requirements — without proxies, offshore inference, or third-party API round-trips.
Session-level KV isolation. On-prem. EU-only. KYC/AML triage, trading-floor copilots, contract analytics — inside your perimeter.
Patient data stays in your infrastructure. Ambient clinical scribing, radiology triage, trial-data extraction — beside your PACS and EMR.
Air-gapped. Regional-rules-ready. Fully auditable. Defense, tax, judiciary, and critical-infrastructure workloads that can’t depend on a foreign endpoint.
The substrate agentic workflows actually need. Stateful inference that keeps multi-step reasoning economically viable at enterprise scale.
Control requires ownership. Ownership does not require complexity. Let us show you what sovereign AI inference looks like when it's designed from the runtime up — not bolted on.