The World’s First Real-time Codeless Reengineering Service for GPUs

Reduce costs. Boost performance. Minimize complexity. No code changes.

As memory becomes the bottleneck, execution efficiency becomes the advantage.

See why GPU optimization is critical

The World’s First Real-time Codeless Reengineering Service for GPUs

Reduce costs. Boost performance. Minimize complexity. No code changes.

See why GPU optimization is critical

Hyperscaler Validation

20–62× Faster • 90–99% Less Energy • Zero Code Changes

These gains come from eliminating wasted execution and memory pressure — not from increasing raw compute.

Independently validated on Amazon Web Services (AWS) and testing underway on Oracle Cloud Infrastructure (OCI), Chameleon delivered dramatic performance improvements and

energy reductions without requiring any changes to customer workloads.


The Challenge

  • Rising cloud GPU compute costs
  • Under-utilized GPUs and performance ceilings
  • Memory stalls and inactive execution paths limiting throughput
  • Workload portability across GPU types and clouds

Hyperscalers needed a breakthrough that delivered instant performance gains without modifying applications.

The Solution: Chameleon®

Chameleon uses the Essence® platform to generate hardware-tuned machine instructions in real-time as Composite Job Designs (CJDs).

  • Real-time SPIR-V generation (no CUDA dependency)
  • Hardware profiling for optimal instruction paths
  • Unified CJD bitstreams — no traditional binary blobs
  • Runs across NVIDIA, AMD, Intel, and other accelerators via SPIR-V–based execution paths
  • No code changes required

AWS & OCI Pilot Results

20–62× Faster
90–99% Less Energy
Similar Gains on AWS & OCI
Portable Across GPU Types
A10G / T4 / L4 / A100 Validated

Results validated using standard GPU telemetry (NVIDIA SMI) alongside chip-time measurements reported by the Chameleon runtime, collected on live cloud GPU instances.


Lower Spend

Teams spending $100K/month on GPUs can often reduce costs to $10K–$25K/month while increasing throughput.

Higher Throughput

Dramatically faster runtimes enable more simulations, more experiments, and faster iteration on existing GPU fleets.

Future-Proof Flexibility

Port workloads across GPU families, instance types, and clouds without refactoring.

Sustainability Gains

Up to 99% less energy per workload dramatically reduces the carbon footprint of compute-intensive workloads.


Access the Chameleon ROI Calculator

Enter your work email to view ROI projections for your deployment.


Not just another AI code tool or profiler

Solution, not suggestion

Generates optimal chip-level or intermediary
instructions directly, eliminating waste

Compounding value

Ensure durable returns by
removing need for source code

Performance compliance

Deliver fully compliant executables
to achieve performance goals

Chameleon® Pilot Program

Experience how Chameleon optimizes workloads for GPUs, CPUs, and TPUs from a wide variety of vendors without requiring changes to existing CUDA, ROCm, OneAPI, or PyTorch–based code.

Step 1: Watch the short overview videos below.

Step 2: Then choose how you want to get hands-on:
download & test locally or run in the cloud (once approved).

This pilot isn’t just for technologists — it’s built for enterprise teams and partners who demand faster, more cost-efficient,
and more sustainable performance across their infrastructure.

Already proven on 30+ Linux distros and expected to run on 50+, Chameleon will soon extend to leading
cloud platforms directly through the Chameleon website.

Pilot version is for evaluation use only — not for production deployment

Ready to unlock GPU performance, energy savings, and higher utilization?
Request Early Cloud Access →

Video #1

Video #1 — Watch how Chameleon dynamically optimizes visual workloads in real time.

Video #2

Video #2 — See why Chameleon is a breakthrough across GPUs, CPUs, TPUs, and heterogeneous compute.



Where Chameleon Runs

Start today on Linux. Cloud and other environments coming soon.

Public Cloud

AWS
Microsoft Azure
Google Cloud
Oracle Cloud (OCI)

Data Center & Virtualization

VMware
Red Hat
Kubernetes
Docker

Silicon & Accelerators

NVIDIA
AMD
Intel
Arm
Apple
Broadcom
Qualcomm
Imagination

Edge & Mission Environments

ISS / Space Edge
Satellite / Austere Edge
5G / MEC
Rugged / Tactical

Platforms & OS

Arch Linux
Debian
Fedora
SUSE
50+ Linux Distros
Windows
Android
macOS
iOS

For the pilot, Linux is fully supported. Additional platforms are on the roadmap.

Don’t see your platform? Chameleon® is environment-agnostic—and we’re adding more.

Why We Created Chameleon

Untitled4

The challenge

750,000 lines of code left un-compilable overnight

Untitled5

Generate optimized machine instructions

What if we could use our own technology to solve the problem?

Untitled6

The breakthrough

Introducing Chameleon: Transforming intent into execution-ready highly-optimized machine code

Untitled5

Generate optimized machine instructions

What if we could use our own technology to solve the problem?

Untitled6

The breakthrough

Introducing Chameleon: Transforming intent into execution-ready highly-optimized machine code

How Chameleon Works

Provide intent

Describe the behavior in
natural language or submit existing GLSL.

No refactoring. No framework lock-in.

Generate optimized execution

Chameleon analyzes the input and
generates optimized SPIR-V for the target hardware

Continuous adaptation based on real hardware behavior.

Integrate and run

Include the result in your
application to optimize workloads

Works across GPUs, CPUs, TPUs, and heterogeneous systems.

Want a deeper technical breakdown of execution, instruction targets, and integration paths?

Supported Emerging Ecosystem Coverage

Currently Supported (via SPIR-V)

AMD-3

arm

broadcom-2
imagination-3
vivante

Who Benefits Most from Chameleon?

These roles lead the charge in AI, infrastructure, and performance engineering.

ai

AI Engineers

protection

Infrastructure Leads

leadership

CTOs & Founders

compiler

Compiler Architects

gpu

Chip Optimization Teams

Real-World Results

In internal testing, Chameleon achieved 10X to 65X speedups over software baselines—typically between 30X and 42X—on a single laptop, not a GPU cluster.

Unlike typical:

  • 2-2x software optimization
  • 10X traditional GPU acceleration

Powered by adaptively optimizing:

  • Execution speed
  • Memory bandwidth
  • File size
  • Energy efficiency

Chameleon replaces slow, manual tuning pipelines with real-time, machine generated instructions for CPUs, GPUs, TPUs, and more.

  • If your workload was already optimized, an additional 30X boost is transformative
  • When scaled across systems or cloud environments, the compounding gains are economically disruptive
  • These results reflect the ability to replace slow, manual optimization pipelines with real-time, machine-generated auto-tuned instructions

8 Benchmark Results

Workload

Speed up

Download

Preview

Description

Red Nebula

65X

Deep color blending & fade effects

Fireworks

55X

Rapid burst patterns with glow trails

Ocean Wave

40X

Curved motion with transparency

SCE_VOX

38X

Real-time voxel rendering

SCE_SDF

33X

Signed distance field lighting

Warp Stars

25X

High-speed star field movement

Brick Tunnel

10X

Dynamic tunnel scrolling with variable depth

Blue Marble

25X

Simulated starfield with depthbased haze

Optimizations today and in the future.

Best Aligned Workloads

Coming Soon

AI/ML Inference
Kernels
Audio Signal
Processing
Motion Planning for
Robotics
2D Image
Analysis
Benchmark Comparison
Scripts
Physics-Free UI
Interactions
Compressed Data
Formats
Lightweight
Cost Estimations
Static Dataset
Computations
Video Game
Engines
Digital
Twins
Edge
Devices
Real-time
XR
Molecular
Dynamics
Add a
New One

Leveling the playing field for chip makers

Chameleon reduces vendor constraints and expands choice for your customers.

Parity for all
vendors

Optimize workloads freely across chips, regardless of maker

Reduced dependency
on software layers

Using “Meaning” as a universal foundation lowers the need for proprietary stacks

Streamlined hardware
integration

Holistic integration avoids optimization bias or elevated switching costs

trend

Fair access
to features

Deliver optimal performance while upholding fair competition goals

Maximize ROI for your chip investments — including GPUs

Drastically reduce compute costs, energy consumption, and time-to-market

Cut costs

Reduce compute hours and hardware dependence with code that delivers more from existing infrastructure — no refactoring required

Save power

Lower data center and edge energy footprints with performance gains that directly support sustainability goals.

Reclaim Engineering Hours

Eliminate manual performance tuning across product, AI, and infra teams  multiplying impact without expanding headcount.

Launch faster

Get new products and features to market in a fraction of the time — even with fewer resources and smaller teams.

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