Unlock the Power of Private AI with Proxzar.

Proxzar specializes in the top 3 layers where essential business value is created. We build secure AI applications powered by private models and with flexible deployment on private or public cloud. Partner with Proxzar to accelerate growth, gain a competitive edge, and stay in control of your data.

The AI Applications layer sits at the top of the AI stack, translating powerful AI models into real-world business solutions.

At Proxzar, we build custom AI applications on top of our/client private AI models, tailored to specific workflows, use cases, and industries.

This approach ensures high performance, strong data security, and complete ownership—allowing organizations to deploy AI with confidence and turn intelligence into measurable outcomes.

Click here for a list of AI Applications that are built or being built on top of our/client private AI models.

Private AI models are designed and trained on an organization’s own proprietary data, ensuring that sensitive business information remains fully secure and under internal control rather than being shared with external third-party platforms.

Proxzar focuses on delivering private AI solutions that help businesses unlock AI-driven insights while safeguarding data privacy, achieving strong compliance, and minimizing risks related to unauthorized access or regulatory violations.

Public AI models such as GPTx, LLaMAx, or Sonnetx are trained on broad internet or mixed public datasets and typically operate on shared infrastructure where user prompts and organizational data may pass through external servers.

While these public models are powerful and general purpose, they do not inherently protect confidential business information or ensure compliance with strict data regulations.

In contrast, private AI models — like those Proxzar develops — are trained and deployed in secure, controlled environments using the enterprise’s own data, significantly reducing risks of data leakage, unauthorized reuse, copyright exposure, and unpredictable behavior (like hallucinations).

This makes private AI especially valuable for industries with stringent privacy requirements (e.g., healthcare, finance, legal, enterprise operations) and strategic initiatives that demand full data governance and tailored AI behavior.

At Proxzar, the Infrastructure layer is designed to support private AI models with flexibility and control.

We architect and manage AI-ready infrastructure across on-premise, private cloud, and hybrid environments, optimized for GPU workloads and secure data access.

This allows organizations to deploy AI models close to their data, meet regulatory obligations, and scale confidently without relying on shared, third-party platforms.

By aligning infrastructure with AI and business needs, Proxzar ensures that models perform consistently, securely, and at enterprise scale.

The Semiconductor (Chips) layer forms the foundation of the AI stack, providing the specialized compute required to train and run AI models efficiently.

GPUs, TPUs, and AI accelerators are purpose-built for large-scale parallel processing, high memory bandwidth, and energy-efficient execution, making them essential for deep learning, large model training, and low-latency inference.

While Proxzar does not design or manufacture chips, our AI solutions are engineered to take full advantage of this layer.