The same AI, inside your walls
AVELIN builds its own models and runs them on your GPUs, on-prem or air-gapped. Up to 85% cheaper than OpenAI and Anthropic in our cloud. Up to 10x cheaper on your own hardware. Your data never leaves.
AI went to production. Then came the bill, the wall, and the waste
Three traps hit regulated teams at once. Here is each one, and what AVELIN does about it.
The bill runs away
Agents burn tokens by the thousands, and at frontier prices the bill only climbs. AVELIN routes each task to the right model instead of defaulting to the priciest one, and runs on your own GPUs, so the bill drops instead.
The best models can't come in
The strongest models are cloud-only, and your regulated data can't go there. AVELIN installs the same frontier-class models inside your walls, so the best AI is finally allowed in.
You overpay on every call
Most requests don't need a frontier model, yet everything defaults to the top tier. AVELIN's trained routing picks the right model per task, so you stop paying for capability you don't use.
Not "cloud-friendly." Inside your walls
AVELIN was built for industries where a data leak is more than a fine. Every component protects your data, ensures reliability, and delivers intelligence you can actually trust.
Your apps and data sit inside your perimeter. AVELIN's Cross-Model MoE runs inside the same boundary. The answer comes back without a single byte leaving your walls.
Your data stays inside
Completely cloud-agnostic. Deploy inside your VPC, on-premise servers, or fully air-gapped. Nothing leaves your control.
Private by architecture
The router reads each request as a numeric vector, not stored text, and zero-retention mode keeps conversation history in memory, never written to disk. There is no raw log of your data to leak.
Failsafe by design
If one model degrades, the system routes to another automatically. Nine specialists, 99.97% uptime, no single point of failure.
The frontier labs stay in their cloud. We run inside your walls
Cloud providers can't come inside your perimeter. AVELIN was built to start there, and the longer it runs, the more it becomes part of how your business works.
The big labs won't sell what we sell
OpenAI and Anthropic make their money renting access to models in their own cloud. Letting you install those models on your own hardware would work against that, so they have little reason to. AVELIN was built the other way around: our models are made to run inside your perimeter, and that is where they stay.
Your AI keeps getting better, on your own hardware
On-prem usually means a model frozen the day it went in. AVELIN is different: when a stronger model ships from anyone, we benchmark it and fold it in within 48 hours, so your intelligence keeps rising with the whole market, with no migration on your side.
Deploy it where your data lives
Run AVELIN in our cloud, on-prem, or fully air-gapped. You choose where it lives, and what leaves your perimeter: nothing.
Cloud
Hosted in our EU cloud. You switch in two lines of code, and we run the infrastructure for you. Up to 85% cheaper than OpenAI and Anthropic, model class for model class.
On-premises
The same models inside your own data center, on your hardware and your network. Up to 10x cheaper per token on your own GPUs, and nothing leaves your walls.
Air-gapped
Fully network-isolated, with no internet required. For the environments where 'almost secure' isn't a category.
Built for compliance, not retrofitted
The EU AI Act is now law, with fines reaching 7% of global revenue. The controls it demands are built into AVELIN, not added once you're live.
Ready for the rules you answer to
HIPAA, GDPR, the EU AI Act, SOX, and FedRAMP are handled from day one, so adopting AI doesn't open a new compliance project.
Your data stays in its jurisdiction
Processing happens wherever you deploy, so nothing crosses a border it shouldn't. No residency workarounds, no legal grey areas.
Access and audit you can prove
Role-based access reaches down to specific datasets and model tiers, and every interaction leaves an audit trail you can hand to a regulator.
Retention on your terms
Zero-retention mode keeps conversation history in memory and off disk, so you decide what persists and what never touches storage.
Where failure is more than a fine
If your industry handles sensitive data, your AI vendor is either part of the solution or part of the risk. AVELIN was built for the sectors where "good enough" gets people fired.
Run it on your own hardware
Request a POC to discuss deploying AVELIN inside your perimeter, on your GPUs, under your compliance. When regulated AI runs inside its own walls, AVELIN is the layer it runs on, the way the private cloud runs on VMware and Red Hat.
Questions about the sovereign platform
What is a sovereign AI platform?
A sovereign AI platform means you, not a vendor or a cloud, decide where the system runs and who can reach it. With AVELIN, the platform runs on GPUs you control, with your data and your prompts inside your network. That is an on-premise LLM stack with data residency you control.
What is included?
Three parts: the AVELIN inference layer that runs the models on your GPUs, the nine AVELIN models, and the API platform. The API platform adds an API compatible with OpenAI and Anthropic clients, speech-to-text, text-to-speech, web search, web scraping, an observability and cost-control platform and user management. The Decision Layer can sit on top.
How is it optimized for our GPUs?
The AVELIN inference layer is optimized at GPU level for the nine AVELIN models, so your hardware generates tokens efficiently. The GPU class and the number of GPUs depend on the tiers you run, and the written scope states both.
Can the models be tuned to our workflows?
Yes. For enterprise customers the models can be fine-tuned or trained on specific workflows. The written scope states the workflow, the data used and how success is measured.
Do we need the Decision Layer?
No. You can use the nine models on their own. They are tuned to work with the Decision Layer, which picks the model each request needs, and a POC of the Decision Layer is a common way to start.
Who can access a deployment on our GPUs?
You decide who can reach it. The written scope lists every network path the software opens and whether each is on or off, and how any vendor support access is granted.
How is it priced?
A deployment on your GPUs is priced by agreement in the written scope. In AVELIN Cloud the nine models have public list prices, from $1.14 to $12.50 per 1M output tokens.
How does a deployment start?
With a POC on one workload, then a written scope, then the install on your GPUs.