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Xinity

Explore Xinity Runtime's features : OpenAI-compatible API, on-premise deployment, model routing, audit logging, and EU AI Act compliance dashboard. Built for European enterprises in regulated industries.

Xinity

Xinity Reviews and Details

This page is designed to help you find out whether Xinity is good and if it is the right choice for you.

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  • Xinity Landing page
    Landing page //
    2026-07-09

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Questions & Answers

As answered by people managing Xinity.
  1. How would you describe the primary audience of Xinity?

    Regulated European enterprises where data sovereignty and compliance are non-negotiable: finance, healthcare, legal, public sector, etc. These are organizations currently unable to adopt cloud AI because doing so would breach sovereignty requirements.

  2. What makes Xinity unique?

    Existing solutions force a binary choice: cloud APIs that violate data sovereignty requirements, or raw open-source tools that require dedicated MLOps teams to operate. Xinity eliminates this tradeoff. Its Scalable On-Premise LLM Management Automation System lets enterprises deploy production-grade generative AI on their own hardware, with OpenAI-compatible APIs, automated orchestration, and deployment in days rather than months. Existing applications can be redirected to on-premise inference with a single line of code. It is sovereign by architecture, not by contract.

  3. What's the story behind Xinity?

    Xinity was founded in 2025 in Vienna by Alexander Zehetmaier (CEO) and Jonas Vander (CTO), who have built AI systems together for over a decade and studied AI at Radboud University in the Netherlands. They saw European companies forced into an impossible choice between powerful cloud AI that violated data sovereignty and open-source tools that were too complex to run without dedicated teams. Xinity was built to eliminate that tradeoff. On April 1, 2026, the company open-sourced its core Runtime under Apache License 2.0, making sovereign AI infrastructure freely available to developers across Europe. The mission: a compute-independent Europe.

  4. Why should a person choose Xinity over its competitors?

    Most competitors sell contractual sovereignty. EU-region hyperscaler offerings and European sovereign cloud operators still process your data on infrastructure they operate, so sovereignty rests on a jurisdiction clause, not physics. That clause does not override CLOUD Act reach, and your data still leaves your perimeter. Xinity is sovereign by architecture: the model runs on hardware inside your perimeter, so no data leaves and no third party can access it. Against raw open-source tooling, which needs a dedicated MLOps team, Xinity adds production-grade orchestration, one-line migration, and a fully auditable Apache 2.0 codebase.

  5. Which are the primary technologies used for building Xinity?

    Xinity is built on Bun and TypeScript. The core packages are an OpenAI-compatible API gateway, a model runtime daemon that runs on the GPU hardware, an operator CLI, a model registry (infoserver), and a SvelteKit admin dashboard. vLLM serves as the inference backend, with the data layer on Drizzle ORM, environment validation via Zod, and logging via Pino. It deploys through Docker Compose, with NixOS support. The proprietary R&D layer is Distributed Split Inference using a Mixture-of-Experts architecture, where expert sub-networks run across separate compute nodes and embedding encoding prevents any single node from reconstructing the output. The engine (gateway, daemon, CLI, infoserver, DB layer) is Apache 2.0; the dashboard is source-available under Elastic License 2.0.

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Is Xinity good? This is an informative page that will help you find out. Moreover, you can review and discuss Xinity here. The primary details have been verified within the last quarter. So they could be considered up to date. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.