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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, Drupal seems to be more popular. It has been mentiond 28 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.
I would be interested in some good migration tools, paid ones are also ok. I found a post about this on drupal.org, but it didn't seem like an easy process. It is a multilanguage site with many content types, and a totally custom theme. Source: over 3 years ago
You got already good advice, but wanted to point the guide of drupal.org where you can see some tools listed with instructions and channels https://www.drupal.org/community/contributor-guide/reference-information/talk/tools. Source: over 3 years ago
There is a service call GitPod that provides a temporary container Drupal environment. If you are familiar with what is going on around the future of how Drupal modules will eventually be offered up, you will likely have seen the "Project Browser" module as a contrib demo of the approach. It is used for people to give feedback to the developers. So they set up the typical 'SimplyTestMe' but also a GitPod... Source: almost 4 years ago
For reviews, it depends entirely on what you mean by "review". I believe core has a simple comment module, although it may have been deprecated for D9? There are likely many review-style modules on drupal.org that might work, or if you just want to link out to third-party reviews then it could just be a repeating-value link field on the Product content type. Source: almost 4 years ago
They should also use standards tools like Github. The drupal.org platform was certainly impressive 10 years ago, today it's a pain to use it. They ducktape it with gitlab, but really it sucks to have to read documentation to simply do a pull request. Source: almost 4 years ago
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