EXdeck.xyz's answer

EXdeck generates real, fully editable files — not locked previews or watermarked exports. You get native .pptx, .xlsx, and document formats you can open directly in PowerPoint, Word, or Excel, with no paywall blocking the download. It's built mostly client-side, keeping it fast and affordable, and includes Collaboration Mode with owner/editor/viewer roles and change history — so teams can work on files together, not just generate them solo.

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.

EXdeck.xyz's answer

Students, early-career professionals, and small teams who need to quickly produce polished presentations, documents, and spreadsheets but don't want to pay for expensive software or deal with restricted exports. Also useful for solo founders and freelancers who need professional-looking files fast.

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.

EXdeck.xyz's answer

Many AI presentation/document tools give you a preview and then charge extra or watermark the file when you try to export. EXdeck's exports are real and unrestricted from the start. It also covers more ground in one place — presentations, documents, spreadsheets, resumes, and file conversion — at $1.99/month, well below what most competitors charge for editable exports alone.

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.

EXdeck.xyz's answer

EXdeck started as a solo project to solve a personal frustration: most AI file-generation tools either lock the real export behind a paywall or produce files that aren't truly editable. It's built and maintained by a single developer, with a focus on shipping real, usable output rather than flashy demos.

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:

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.