The AI GPU performance engineer
Profiles, diagnoses, and optimizes your GPU code. From kernels to models, runtimes, and entire inference pipelines






Runs real profilers on your code. NSight Compute, ROCProfiler, PyTorch Profiler, and more.
Reads traces and finds the bottleneck. Cross-references profile, docs, and code to explain what's slow and why.
Writes and validates the fix. Generates optimized code and checks PTX, SASS, and IR to verify the change at the compiler level.
Runs on real GPUs. On-demand environments for profiling, benchmarking, and testing on actual hardware.
Agent-native access to all the tools for the full performance loop.
The Wafer agent has its own profiler, compiler analyzer, docs and more.
Runs NVIDIA Compute Utility to collect hardware counters and identify optimization targets.
Full AMD GPU profiling support. One agent across both NVIDIA and AMD hardware.
Collection of GPU guides and optimization best practices to ground its recommendations.
Inspects PTX and SASS output from your CUDA code to verify optimizations at the compiler level.
Interprets profiler output and extracts actionable insights, not just raw numbers.
Review the agent's proposed changes before applying. Accept, reject, or modify.
Runs reproducible benchmarks before and after every change to verify speedups.
Control how much the agent does on its own. Step-by-step approval or fully autonomous.
Simple, transparent pricing
Start free, scale as you need. Credits work for both AI agent calls and GPU compute time.
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