The fastest hardware still needs efficient code

Find performance bottlenecks in the code you already run. Test a multitude of possible optimizations against your baseline on your target hardware. Apply only the changes that deliver measurable improvements.

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Per-hash latency, ns

Baseline0 ns
Artemis0 ns

−14%

Firedancer Solana validator client · AMD EPYC 9B45

More than just faster code.

Delay infrastructure spend

Run more work on the same infrastructure before you need to scale out.

Lower latency

Reduce execution time for the workloads where every millisecond matters.

Free up engineering time

Artemis explores the optimization space automatically, so engineers can focus on building products.

Results validated across trading, banking and blockchain systems

The same optimization process delivers measurable improvements across trading systems, banking infrastructure, and the validator clients that power blockchain networks.

−14%per-hash latency (768 → 660 ns)
Solana validator
Firedancer LtHashAMD EPYC 9B45AVX-512C++
+32.7%faster runtime
QuantLib
Open-source quantitative finance libraryC++
−42%latency reduction
Trading inference stack
Leading HFT firmInternalC++
+22%faster runtime
Enterprise financial system
Pan-African bankProprietary quant librariesCPU

Every nanosecond counts

A hot path runs on every request. Saving a few nanoseconds per execution translates into significant compute savings over time.

Artemis
The hot pathhashing, serialization, whatever sits on the critical path+22% faster
One call on the critical pathcounted in microseconds, not milliseconds
Every request that touches itnothing above it has to change
The latency budget you promisedan SLA, a tick-to-trade window, a control-loop deadline

Explore more. Measure every change. Own the result.

Explore hundreds of possible implementations

Generate hundreds of candidate implementations and benchmark each one against your baseline on your target hardware. Keep only the changes that improve performance.

runtime (ms)

faster

searching candidates…

Only proven improvements make it through

Every candidate must improve performance and produce the correct result before your team reviews it. Anything that fails either test is discarded.

BaselineCandidate
checking output…
measuring speed…

The optimized code is yours

The result is a pull request against your repository. Your team reviews the diff and merges the changes. The optimized code stays with you.

preparing diff…
- baseline implementation
+ optimized implementation

delivered as a pull request

Common questions.

Artemis handles the breadth your engineers don't have hours for, testing hundreds of implementations in parallel while they stay on the work that needs their judgment. Your team can start and steer Discovery runs from the Artemis CLI or from the coding agent they already use, and nothing merges without someone approving the diff.

See how much latency you can cut.

Point Artemis at the code on your critical path, and see the tail-latency improvement it finds, validated, before you change a thing.

Get a custom benchmark