Run frontier LLMs on sovereign EU infrastructure

guillego1 pts0 comments

Models

" fs-copyclip-element="click" fs-copyclip-message="Copied to clipboard" class="sub-nav-item">Copy Logo as SVG

Visit Brand Kit

Solutions

Developers

PricingResources

Company

Log inSign up

Coding Apps Websites Shield Lock Streamline Icon: https://streamlinehq.com coding-apps-websites-shield-lock<br>Your code never leaves Europe

Coding Apps Websites Programming Browser Streamline Icon: https://streamlinehq.com

coding-apps-websites-programming-browser

20% faster inference, with no accuracy tradeoff

Design Layer Streamline Icon: https://streamlinehq.com design-layer<br>Compliant, verified, and secure, down to the GPU

Business Products Performance Money Decrease Streamline Icon: https://streamlinehq.com business-products-performance-money-decrease<br>Cut AI coding spend up to 10x

No operational control

Inference location, security, and underlying changes sit with the provider - not with you.

One-vendor lock-in

Prompts and workflows harden around a single API. Unwinding costs more than building did.

Costs you can't forecast

Rates and limits move on their schedule, so capability gets rationed to budget.

Foreign jurisdiction

Contract and access terms can shift with a political decision, not a commercial one.

Path 01

Agentic coding in the terminal

Point OpenCode, ForgeCode, Crush, or Pi at Corti Models with the Corti CLI. Keep the workflow you already have.

# run the setup wizard<br>npx @corti/cli init models<br># load credentials, then launch your agent<br>set -a; source ~/.env; set +a<br>opencode

Path 02

Direct API in your product

OpenAI-compatible. Existing app code works with a base URL change and a new key.

client = OpenAI(<br>base_url="https://ai.eu.corti.app/v1",<br>api_key="")<br>r = client.chat.completions.create(<br>model="corti-s1", messages=msgs

Model<br>Best for<br>Reasoning<br>Cost per 1M tokens

corti-s1 Recommended<br>Complex agentic coding and repo-wide refactors<br>Yes<br>$2.00 in · $8.00 out$0.20 cached input

corti-s1-instant<br>Fast interactive coding and inline completion<br>No<br>$2.00 in · $8.00 out$0.20 cached input

corti-s1-mini<br>High-volume review, tests, and refactors at lower cost<br>Yes<br>$1.00 in · $4.00 out$0.10 cached input

corti-s1-mini-instant<br>Cost-sensitive completion at scale<br>No<br>$1.00 in · $4.00 out$0.10 cached input

corti-s1-embedding<br>Codebase search, retrieval, and indexing<br>n/a<br>$0.03 inno output charge

A working prototype

Someone on your team builds the feature against OpenAI or Anthropic. It demos well. The business case is obvious.

Security, legal, procurement

Data residency cannot be answered. The transfer cannot be justified. The cost at scale cannot be approved. The feature sits in review and the quarter ends.

The same code, cleared

Change the endpoint and the credentials. Keep your application logic, your prompts, and your evaluation set. Run it on infrastructure that passes review the first time.

Verifiable

Verifiable at every layer

Most vendors claim sovereignty in the contract, then rent the stack. Corti Models runs on Kommodity, an open source infrastructure layer, so the entire stack, including encryption, isolation, and security, is public and auditable, not just claimed.

Attestation before inference - isolation enforced by hardware, not policy<br>No US cloud provider in the request path<br>Infrastructure code open source on GitHub for anyone to review

Explore Kommodity on Github

Request traceEU-CPH

10:24:07.004 request receivedeu-copenhagen

10:24:07.006 attestation verifiedquote ok

10:24:07.009 routed to nodegefion / n-04

10:24:07.011 model loadedcorti-s1

10:24:07.788 completion returnedeu-copenhagen

10:24:07.789 prompt retainednone

10:24:07.789 used for trainingnever

Private

Private by architecture

Prompts and completions process in memory and end with the request. Nothing is retained, nothing trains a model, nothing is visible to another tenant.

Central control over access, data handling, and per-team budget<br>Sovereign cloud or on-premises - same platform as clinical AI in production<br>ISO 27001, ISO 42001, GDPR, NIS2, DORA, and EU AI Act posture by default

GovernanceDefault

Prompt retention<br>none

Training on your data<br>never

Data residency<br>your region

Deployment<br>cloud / on-prem

Usage reporting<br>per team

Capacity management

Monitoring and observability

Failover and resilience

Tool calling

Structured outputs

Prompt caching

Access controls

Auditability

Model evaluation

Managed model upgrades

Predictable pricing

Enterprise support

Today’s leader isn't tomorrow’s

Corti evaluates and operates the best available models as the market moves - without you rebuilding integrations every leaderboard cycle.

Economics

Pay for tokens, not seats

Per-seat coding assistants charge whether developers use them or not. Governed consumption charges for what runs, at European infrastructure cost.

One credit balance across Corti APIs<br>Same credits for development, testing, and production<br>Per-team limits and request-level reporting

EstimateDirectional

Developers with AI...

corti coding model infrastructure models https

Related Articles