One method, wherever you can measure the result
Artemis takes code you already run, writes many candidate versions of it, then builds and benchmarks every one on your own hardware and keeps only the versions that measurably win. That loop does not care what the code does, which is why the same platform improves an inference stack, a SQL pipeline and a delivery-routing algorithm. Your domain enters as the benchmark.
Pick the number you
are judged on
Faster
Throughput and latency, from the serving stack down to the inner loop. Artemis found 2.07× the output token throughput for vLLM on Intel Xeon 6 in a build Intel formally approved, and a 40% gain NVIDIA merged into TensorRT-LLM.
Cheaper
The same work on a smaller bill: fewer tokens per agent run, fewer warehouse credits per query, more users per machine you already own. A global investment firm cut the credits its Snowflake pipelines burn by 75%.
Better
Accuracy is a metric like any other, and so is a business objective. A major UK bank kept five production models — fraud detection, risk and others — that scored better on its own measure, with nothing else given up.
Not sure which of these is your biggest number?
Bring one metric, one repository and one benchmark. That is everything a pilot needs. Artemis also works on platform and middleware builds, stands guard on a benchmark once you have set it, and runs fully on-premise or air-gapped when the code cannot leave.