Low-Level AI Infrastructure

Build kernels.

Scale inference.

Fabricate the future._

Stop wrestling with CUDA and Triton. Write, compile, and deploy optimized kernels — all in one platform.

<5ms kernel launch
multi-GPU ready
K8s native
Trusted Tech Stack
CUDATensorRTvLLMTritonPyTorchMetalROCmONNX CUDATensorRTvLLMTritonPyTorchMetalROCmONNX
root@kernelfab:~$ ./compile.sh --optimize
# Initialize KernelFab runtime environment
import kernelfab as kf
 
kernel = kf.compile("matmul_fused.cu", arch="sm_90")
# => Compiled in 234ms, 4.2x faster than torch
 
@kf.jit
def inference(x):
    return kernel(x)
 
result = inference(batch)
# [OK] Kernel launched in 3.8ms | GPU: H100 | Mem: 2.1GB_

Generic tools vs. KernelFab platform.

See the difference when you build on infrastructure made for kernel engineers.

Generic Generic Kernel Tools

Most teams stitch together CUDA, Triton, and custom scripts � then spend weeks debugging memory leaks and sync issues.

  • ? No unified pipeline
  • ? Manual memory management
  • ? No built-in profiling
  • ? Poor multi-GPU support
  • ? Deployment headaches
KernelFab KernelFab Platform

One platform that compiles, optimizes, and deploys your kernels with hardware-aware scheduling and real-time profiling.

  • ? Unified compile ? deploy pipeline
  • ? Automatic memory optimization
  • ? Built-in flame graphs & tracing
  • ? Native multi-GPU, K8s ready
  • ? One-command deploy with rollback

Everything for your kernel stack.

From CUDA to production. No wrappers, no bloat — just raw performance.

K

Kernel Forge

Write CUDA, Triton, or Metal. Auto-tune for H100, MI300, and custom ASICs with a single command.

nvcctritonmetal
I

Inference Engine

Sub-5ms cold starts. Dynamic batching, KV-cache optimization, and tensor parallelism built-in.

vLLMTensorRTC++
D

Deploy Fabric

K8s native. Multi-region, auto-scale, zero-downtime deploys with hardware-aware scheduling.

k8shelmterraform
O

OptiView

Real-time kernel profiling. Flame graphs, memory tracing, and bottleneck detection out of the box.

profilingtracingmetrics
M

Model Hub

Pre-optimized kernels for Llama, Mistral, and GPT architectures. One-line integration.

llamamistralgpt
S

Secure Sandbox

Isolated kernel execution with seccomp, namespaces, and GPU partitioning for multi-tenant safety.

seccompcgroupsGPU

Benchmarks that matter.

Raw numbers from production-grade H100 clusters running real workloads.

4.2x
vs PyTorch Eager
matmul fused kernel
<5ms
p99 cold start
H100 → first token
3.8x
throughput / GPU
Llama 70B INT4
99.99%
uptime SLA
production grade

Built for scale.

A unified pipeline from kernel source to production inference.

</>
Source
CUDA / Triton / Metal
Compile
Forge Engine
📊
Optimize
Auto-tune
🚀
Deploy
Fabric CD

Built for real workloads.

KernelFab.com adapts to every layer of the AI infrastructure stack.

01

LLM Inference API

Deploy optimized kernels for large language models with sub-10ms latency and dynamic batching across GPU clusters.

02

Custom Kernel Tooling

Sell proprietary CUDA/Triton kernels with a marketplace and CI/CD pipeline for kernel developers.

03

GPU Cloud Platform

Multi-tenant GPU compute with kernel-level isolation, resource quotas, and per-tenant optimization.

04

AI Research Lab

Rapid prototyping of novel attention mechanisms, custom operators, and experimental kernel architectures.

Monitor your kernel performance.

Real-time metrics, flame graphs, and deployment status � all in one view.

root@kernelfab:~$ htop --kernel
KERNEL LATENCY
3.8ms
p99 cold start
THROUGHPUT
4.2x
vs PyTorch Eager
GPU UTIL
94.7%
H100 cluster avg
UPTIME
99.99%
SLA compliance
Kernel Launch Latency (24h)
[2026-05-07 14:23:11]
kf_compile: matmul_fused.cu ? SM90 binary (234ms)
[2026-05-07 14:23:12]
kf_deploy: deployed to H100 cluster (3 nodes)
[2026-05-07 14:23:15]
kf_bench: 4.2x speedup vs baseline
[2026-05-07 14:25:03]
kf_mem: high VRAM usage detected (8.2GB/80GB)
[2026-05-07 14:25:04]
kf_optimize: auto-tuned for batch_size=32
[2026-05-07 14:30:22]
kf_health: all 3 nodes healthy
[2026-05-07 14:35:41]
kf_scale: auto-scaled to 5 nodes
[2026-05-07 14:40:18]
kf_bench: sustained 3.8x throughput
PREMIUM DOMAIN

KernelFab.com is available

Perfect for low-level AI infrastructure, kernel compilers, GPU cloud platforms, or developer tools. Serious inquiries only.

root@kernelfab:~$ domain --acquire
# Initiating domain acquisition protocol...
 
> Connecting to registrar...
[OK] Connected to Spaceship/Afternic
> Verifying domain availability...
[OK] KernelFab.com is available
> Checking premium status...
[OK] Premium domain confirmed (Grade A)
 
! This domain is in high demand
> Preparing purchase options...
[OK] Ready. Contact below to proceed._