AI Inference Platforms
High-throughput LLM and generative-AI serving.
AI Inference Silicon / Architecture & Prototype Development
Compute, reimagined for inference.
BERNION is a specialized compute architecture built from the ground up for modern AI inference workloads.
Not general-purpose. Not repurposed. Purpose-built, for the operations, data movement, memory utilization, and numerical formats that drive today's neural-network inference.
Who BERNION Is For
Purpose-Built for the Inference Era
BERNION™ X1 is being designed for AI inference providers, private AI infrastructure, enterprise data centers, and next-generation AI servers. From LLM serving and RAG to AI agents and high-concurrency generative AI, BERNION focuses on the workloads where cost per token, performance per watt, memory efficiency, and predictable latency matter most.
Enterprise & Private AI
Efficient inference for secure on-premise and private-cloud deployments.
AI Servers & OEMs
A purpose-built accelerator foundation for dedicated inference systems.
BERNION's goal: make every watt and every dollar of AI infrastructure produce more useful inference.
See the full use-case breakdown →Why Purpose-Built
Most compute architectures were designed to do everything reasonably well. BERNION is designed to do one thing exceptionally well: run AI inference, efficiently, at scale.
By focusing exclusively on the demands of transformer-based models (matrix and tensor operations, low-precision math, memory bandwidth, and massive parallelism), BERNION aims to deliver a fundamentally more efficient path from model to output.
General-purpose compute
BERNION: purpose-built array
Architecture Focus
Five commitments, one workload.
Transformer-Optimized Compute
A compute architecture designed around the matrix and tensor operations that power transformer-based AI models, the backbone of modern generative AI.
Low-Precision Acceleration
Planned support for efficient INT8 and INT4 inference, unlocking higher computational efficiency and reduced memory requirements without compromising the workloads that matter.
Memory-Aware Architecture
Engineered to minimize unnecessary data movement and maximize utilization of available memory bandwidth, because in inference, memory is often the real bottleneck.
Parallel AI Execution
A highly parallel compute design built to accelerate neural-network inference at scale.
High-Speed Host Connectivity
Planned high-bandwidth interfaces for seamless integration into AI servers and modern compute infrastructure.
BERNION X1
Preliminary design targets.
Datasheet / Draft 0.1
Preliminary
| Processor Type | AI Inference Accelerator |
|---|---|
| Primary Workloads | Transformer / Generative AI |
| Compute Precision | INT8 / INT4 |
| Architecture | Specialized Tensor / Matrix Compute |
| Host Interface | PCI Express |
| Memory Architecture | High-Bandwidth Optimized |
| Primary Optimization | Performance / Watt / Cost |
| Development Stage | Architecture & Prototype Development |
Specifications shown are preliminary design targets and may change during development and validation.
Hardware + Software Co-Design
Silicon alone isn't enough.
BERNION is being developed as a fully integrated hardware and software platform, so performance on paper translates into performance in production.
BERNION Silicon
BERNION Runtime
BERNION Compiler
BERNION SDK
AI Frameworks
Hardware-aware software optimization is being built in at every layer, so AI models can efficiently utilize the full depth of the BERNION architecture, not just its peak theoretical throughput.
Our Performance Philosophy
Raw compute numbers don't run your business.
Tokens per Second
Raw throughput, where it counts.
Tokens per Watt
Efficiency, at scale.
Tokens per Dollar
The metric that determines what's actually viable.
BERNION development is centered on three measurements that matter in the real world: tokens per second, tokens per watt, and tokens per dollar.
Our objective isn't simply to chase higher theoretical compute performance. It's to improve the real-world economics of AI inference, for every model, every deployment, every dollar spent.
About the Founder
BG
Bernard G is a technology entrepreneur and software architect with more than two decades of experience across software engineering, cloud infrastructure, enterprise technology, and artificial intelligence.
His work spans AI systems, cloud architecture, cybersecurity, data platforms, and enterprise software, with hands-on experience across AWS, Microsoft Azure, Kubernetes, Python, and modern AI/ML infrastructure.
Bernard founded Vgosh Info to build technology products that combine practical engineering with emerging advances in artificial intelligence. With BERNION, he is leading the company's expansion into AI semiconductor technology, with a vision to develop purpose-built processors that improve the performance, energy efficiency, and economics of AI inference.
The next generation of AI will require not just more computing power, but more intelligent computing architecture.
Get in Touch
Currently in architecture and prototype development.
If you're building AI infrastructure and want to follow our progress, or explore early collaboration, we'd like to hear from you.