Our Work

Our Projects

A collection of visionary projects spanning AI-native computing, cross-platform applications, and the Deepcomet AI ecosystem. Building the future of intelligent software.

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Deepcomet AI Ecosystem

Core Ecosystem Projects

The foundational technologies powering the next generation of AI-native computing.

Aurelia Language

An AI-native systems programming language with first-class tensor primitives, automatic differentiation, and direct MLIR compilation targeting NPUs. The core of the Deepcomet AI stack.

Systems ProgrammingMLIRAI/MLCompiler DesignNPU

Zenith Kernel

A microkernel with probabilistic scheduling that predicts resource needs 10ms in advance and an AI-Watchdog immune system for intrinsic zero-day exploit protection.

MicrokernelProbabilistic SchedulingSecurityAI-Watchdog

SkyOS

A generative operating system powered by Large Action Models. Instead of static interfaces, SkyOS generates the optimal experience for every task in real-time.

Operating SystemsLarge Action ModelsGenerative UIAI-Native

The Forge

AI-powered automated migration tooling that transpiles legacy C++ and Java codebases to idiomatic Aurelia. Not just syntax conversion — semantic understanding and optimization.

TranspilationAI MigrationC++JavaAurelia
Applications

Application Projects

Cross-platform applications and tools built with modern technology stacks.

GeminiChat

A cross-platform chatbot application powered by Google's Gemini API. Being developed in two parallel implementations — Nuxt+Tauri and .NET+Avalonia — exploring different strengths in architecture.

Nuxt.jsTauriRust.NETAvaloniaGemini API

This Website

The site you're viewing now — built with Astro SSG, MDX support, and a dark futuristic UI with neon accents. Islands architecture for minimal JavaScript with interactive components.

AstroMDXSSGDark UIGitHub Pages
Vision

The Deepcomet AI Approach

Why vertical integration matters for the future of AI computing.

01

Language Layer

Aurelia provides the foundational programming model with AI-native primitives. Tensors, automatic differentiation, and NPU targeting are language features, not library add-ons.

02

Kernel Layer

Zenith understands AI workloads at the scheduling level. Probabilistic models predict resource needs before they arise, eliminating latency that plagues general-purpose kernels.

03

OS Layer

SkyOS uses Large Action Models to generate interfaces and execute complex workflows autonomously. The operating system itself becomes an intelligent agent.