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Xinity's answer:
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.
Xinity's answer:
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.
Xinity's answer:
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.
Xinity's answer:
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.
Xinity's answer:
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.
Based on our record, Jekyll seems to be more popular. It has been mentiond 203 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
This is a static site generated with hugo with the PaperMod theme. I wanted an easy to use static site generator. I considered Jekyll And believe it to be a good choice for static sites. There seemed to be slightly more themes I liked with Hugo so I went with that. That's a pretty superficial choice but I also don't plan on hacking on the Site generation itself so I was agnostic to the Go versus Ruby choice. - Source: dev.to / 3 months ago
First of all, I modified my publishing programs to keep a (local) copy of each link published modulePublicationCache and then I thought about using it for my linkblog. I like very much jekyll for a blog and I requested to some AIs (mainly Qwen and Gemini) to help me to develop a blog based on the links I has posted the previous day, prepare a list with them, and prepare a Jekyll post. I also requested to set up a... - Source: dev.to / 4 months ago
I started this blog on WordPress. After several years, I decided to migrate to Jekyll. I have been happy with Jekyll so far. It's based on Ruby, and though I'm no Ruby developer, I was able to create a few plugins. - Source: dev.to / 5 months ago
So, I created โ๏ธ Meddler, a command-line tool and website that will take the .ZIP of your export that Medium gives you and turn it into clean, portable Markdown formats for Jekyll, Hugo, Eleventy, or Astro.js. - Source: dev.to / 5 months ago
After writing your posts in Markdown you can then display them however you'd like on your site through the built in Postwave Ruby client. This is where Postwave differs from static blog engines like Jekyll or Hugo which take the Markdown posts and generate a site for you. - Source: dev.to / 10 months ago
Hugo - Hugo is a general-purpose website framework for generating static web pages.
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