OneStack.AI

AI SYSTEMS & ARCHITECTURE

Rethinking AI
as one system,
from model
to silicon.

Better AI starts with the whole system.
We connect models, software, and hardware
through first-principles co-design.

Explore our approach
ONESTACK.AI / SYSTEM VIEW01—04
One system, four connected layers Models, software, architecture, and silicon are connected by a shared feedback loop. Select a layer below to read about its role. 01020304 CO-DESIGN

Start with the workload.

Model structure, precision, and quality targets shape every decision below.

FIRST PRINCIPLES. SHARED CONSTRAINTS. ONE STACK.SCROLL TO EXPLORE

01 / ABOUT ONESTACK.AI

THE WHOLE SYSTEM MATTERS

One system.
Every layer.

The best AI system is designed together.

OneStack.AI is an AI systems and architecture company focused on vertical co-design: connecting model decisions to the software and silicon that execute them.

We start with the workload and its constraints. Then we work across abstraction boundaries to align model quality, latency, throughput, energy, and cost.

[01]

First principles

Understand the workload. Identify the limiting resource. Build from measurable constraints.

[02]

Cross-layer integration

Connect decisions across the stack. Treat interfaces, data movement, and feedback as part of the design.

[03]

System-level evidence

Evaluate the complete path from model quality to execution efficiency, with explicit assumptions and reproducible measurements.

02 / TECHNOLOGY

MODEL ↔ SOFTWARE ↔ HARDWARE

Co-design across
the entire stack.

From workload analysis to architecture exploration, our focus is the interaction between layers—and what it means for the system.

01 / MODEL

Hardware-aware
AI models

Explore model architectures, quantization, and sparsity in the context of the hardware that will run them.

  • Workload analysis
  • Precision
  • Sparsity
02 / SOFTWARE

Compilers, kernels
& runtimes

Connect model graphs to efficient execution through operator mapping, kernel optimization, and runtime scheduling.

  • Graph lowering
  • GPU kernels
  • Scheduling
03 / ARCHITECTURE

Compute & memory
architecture

Reason about dataflow, memory hierarchy, and parallelism together to expose bottlenecks and compare design choices.

  • Dataflow
  • Memory systems
  • Interconnect
04 / SILICON

Accelerators &
silicon co-design

Translate workload requirements into accelerator concepts, FPGA prototypes, and power, performance, and area trade-offs.

  • FPGA prototyping
  • Accelerators
  • PPA analysis
OUR DESIGN LOOP
  1. Characterize
  2. Co-design
  3. Prototype
  4. Measure
  5. Refine

03 / RESEARCH & PROJECTS

QUESTIONS WORTH BUILDING FOR

Explore the
design space.

Our research agenda centers on practical questions at the boundaries of AI models, systems, and architecture.

R / 01Efficient AI inferenceModel quality · Latency · ThroughputRESEARCH DIRECTION

Where does inference spend its time and energy?

Study the interaction of precision, attention, memory traffic, and batching. Evaluate quality and execution efficiency together, under clearly defined workloads and hardware constraints.

Potential artifacts: workload characterizations, evaluation methods, and optimization studies.

R / 02Workload-driven architecturesDataflow · Memory hierarchy · ParallelismRESEARCH DIRECTION

What architecture does the workload actually need?

Explore how operator structure and data reuse shape compute arrays, memory systems, and interconnect. Make design assumptions explicit and examine sensitivity across workloads.

Potential artifacts: architecture models, design-space studies, and FPGA prototypes.

R / 03Cross-layer evaluationModel-to-hardware mapping · System trade-offsRESEARCH DIRECTION

How do local decisions change the whole system?

Trace model and compiler choices through to hardware utilization and end-to-end performance. Build evaluation approaches that capture the trade-offs hidden by isolated benchmarks.

Potential artifacts: measurement tools, reproducible experiments, and technical notes.

Public projects and publications will be listed here as they become available.

04 / CONTACT

Let's think
across layers.

Research collaborations. Architecture discussions.
Challenging AI systems problems.

START A CONVERSATION

Public contact details will be announced here.